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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted alphabetically
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Argumentation et analyse du discours     Open Access   (Followers: 7)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 12)
Biometrical Journal     Hybrid Journal   (Followers: 9)
Biometrics     Hybrid Journal   (Followers: 50)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Building Simulation     Hybrid Journal   (Followers: 2)
CHANCE     Hybrid Journal   (Followers: 5)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics - Theory and Methods     Hybrid Journal   (Followers: 11)
Computational Statistics     Hybrid Journal   (Followers: 15)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 35)
Current Research in Biostatistics     Open Access   (Followers: 8)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 12)
Demographic Research     Open Access   (Followers: 14)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
ESAIM: Probability and Statistics     Open Access   (Followers: 4)
Extremes     Hybrid Journal   (Followers: 2)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 11)
Handbook of Numerical Analysis     Full-text available via subscription   (Followers: 5)
Handbook of Statistics     Full-text available via subscription   (Followers: 7)
IEA World Energy Statistics and Balances -     Full-text available via subscription   (Followers: 2)
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
International Journal of Quality, Statistics, and Reliability     Open Access   (Followers: 17)
International Journal of Stochastic Analysis     Open Access   (Followers: 2)
International Statistical Review     Hybrid Journal   (Followers: 12)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Applied Statistics     Hybrid Journal   (Followers: 20)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 23)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 38, SJR: 3.664, CiteScore: 2)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 21)
Journal of Econometrics     Hybrid Journal   (Followers: 82)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 7)
Journal of Forecasting     Hybrid Journal   (Followers: 19)
Journal of Global Optimization     Hybrid Journal   (Followers: 6)
Journal of Mathematics and Statistics     Open Access   (Followers: 6)
Journal of Nonparametric Statistics     Hybrid Journal   (Followers: 6)
Journal of Probability and Statistics     Open Access   (Followers: 10)
Journal of Risk and Uncertainty     Hybrid Journal   (Followers: 33)
Journal of Statistical and Econometric Methods     Open Access   (Followers: 3)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 7)
Journal of Statistical Software     Open Access   (Followers: 16, SJR: 13.802, CiteScore: 16)
Journal of the American Statistical Association     Full-text available via subscription   (Followers: 72, SJR: 3.746, CiteScore: 2)
Journal of the Korean Statistical Society     Hybrid Journal  
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 37)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 28)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 41)
Journal of Theoretical Probability     Hybrid Journal   (Followers: 3)
Journal of Time Series Analysis     Hybrid Journal   (Followers: 16)
Journal of Urbanism: International Research on Placemaking and Urban Sustainability     Hybrid Journal   (Followers: 23)
Law, Probability and Risk     Hybrid Journal   (Followers: 6)
Lifetime Data Analysis     Hybrid Journal   (Followers: 7)
Mathematical Methods of Statistics     Hybrid Journal   (Followers: 4)
Measurement Interdisciplinary Research and Perspectives     Hybrid Journal   (Followers: 1)
Metrika     Hybrid Journal   (Followers: 4)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 3)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 8)
Optimization Letters     Hybrid Journal   (Followers: 2)
Optimization Methods and Software     Hybrid Journal   (Followers: 6)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 33)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 15)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 7)
Review of Economics and Statistics     Hybrid Journal   (Followers: 143)
Review of Socionetwork Strategies     Hybrid Journal  
Risk Management     Hybrid Journal   (Followers: 16)
Sankhya A     Hybrid Journal   (Followers: 3)
Scandinavian Journal of Statistics     Hybrid Journal   (Followers: 9)
Sequential Analysis: Design Methods and Applications     Hybrid Journal  
Significance     Hybrid Journal   (Followers: 7)
Sociological Methods & Research     Hybrid Journal   (Followers: 41)
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
Stata Journal     Full-text available via subscription   (Followers: 8)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 28)
Statistical Modelling     Hybrid Journal   (Followers: 18)
Statistical Papers     Hybrid Journal   (Followers: 4)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Statistics and Computing     Hybrid Journal   (Followers: 14)
Statistics and Economics     Open Access  
Statistics in Medicine     Hybrid Journal   (Followers: 126)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 12)
Stochastic Models     Hybrid Journal   (Followers: 2)
Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports     Hybrid Journal   (Followers: 2)
Structural and Multidisciplinary Optimization     Hybrid Journal   (Followers: 12)
Teaching Statistics     Hybrid Journal   (Followers: 8)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TEST     Hybrid Journal   (Followers: 2)
The American Statistician     Full-text available via subscription   (Followers: 25)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 10)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)

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Sociological Methods & Research
Journal Prestige (SJR): 2.35
Citation Impact (citeScore): 3
Number of Followers: 41  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0049-1241 - ISSN (Online) 1552-8294
Published by Sage Publications Homepage  [1174 journals]
  • A Crash Course in Good and Bad Controls

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      Authors: Carlos Cinelli, Andrew Forney, Judea Pearl
      Abstract: Sociological Methods & Research, Ahead of Print.
      Many students of statistics and econometrics express frustration with the way a problem known as “bad control” is treated in the traditional literature. The issue arises when the addition of a variable to a regression equation produces an unintended discrepancy between the regression coefficient and the effect that the coefficient is intended to represent. Avoiding such discrepancies presents a challenge to all analysts in the data intensive sciences. This note describes graphical tools for understanding, visualizing, and resolving the problem through a series of illustrative examples. By making this “crash course” accessible to instructors and practitioners, we hope to avail these tools to a broader community of scientists concerned with the causal interpretation of regression models.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-20T08:30:25Z
      DOI: 10.1177/00491241221099552
       
  • Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for
           Ecological Inference Based on Linear Programming

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      Authors: Jose M. Pavía, Rafael Romero
      Abstract: Sociological Methods & Research, Ahead of Print.
      The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find solutions stemming from the former, with the latter being less active. From the mathematical programming framework, this paper suggests a new direction for tackling this problem. For the first time in the literature, a procedure based on linear programming is proposed to attain estimates of local contingency tables. Based on this and the homogeneity hypothesis, we suggest two new ecological inference algorithms. These two new algorithms represent an important step forward in the ecological inference mathematical programming literature. In addition to generating estimates for local ecological inference contingency tables and amending the tendency to produce extreme transfer probability estimates previously observed in other mathematical programming procedures, these two new algorithms prove to be quite competitive and more accurate than the current linear programming baseline algorithm. Their accuracy is assessed using a unique dataset with almost 500 elections, where the real transfer matrices are known, and their sensitivity to assumptions and limitations are gauged through an extensive simulation study. The new algorithms place the linear programming approach once again in a prominent position in the ecological inference toolkit. Interested readers can use these new algorithms easily with the aid of the R package lphom.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-16T07:43:06Z
      DOI: 10.1177/00491241221092725
       
  • A Language-Based Method for Assessing Symbolic Boundary Maintenance
           between Social Groups

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      Authors: Anjali M. Bhatt, Amir Goldberg, Sameer B. Srivastava
      Abstract: Sociological Methods & Research, Ahead of Print.
      When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining symbolic boundaries: boundary retention—entrenching themselves in pre-existing symbolic distinctions—and boundary reformation—innovating new forms of symbolic distinction. Traditional approaches to measuring symbolic boundaries—interviews, participant-observation, and self-reports are ill-suited to detecting fine-grained variation in boundary maintenance. To overcome this limitation, we use the tools of computational linguistics and machine learning to develop a novel approach to measuring symbolic boundaries based on interactional language use between group members before and after they encounter one another. We construct measures of boundary retention and reformation using random forest classifiers that quantify group differences based on pre- and post-contact linguistic styles. We demonstrate this method's utility by applying it to a corpus of email communications from a mid-sized financial services firm that acquired and integrated two smaller firms. We find that: (a) the persistence of symbolic boundaries can be detected for up to 18 months after a merger; (b) acquired employees exhibit more boundary reformation and less boundary retention than their counterparts from the acquiring firm; and (c) individuals engage in more boundary retention, but not reformation, when their local work environment is more densely populated by ingroup members. We discuss implications of these findings for the study of culture in a wide range of intergroup contexts and for computational approaches to measuring culture.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-13T07:05:12Z
      DOI: 10.1177/00491241221099555
       
  • Who Does What to Whom' Making Text Parsers Work for Sociological
           Inquiry

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      Authors: Oscar Stuhler
      Abstract: Sociological Methods & Research, Ahead of Print.
      Over the past decade, sociologists have become increasingly interested in the formal study of semantic relations within text. Most contemporary studies focus either on mapping concept co-occurrences or on measuring semantic associations via word embeddings. Although conducive to many research goals, these approaches share an important limitation: they abstract away what one can call the event structure of texts, that is, the narrative action that takes place in them. I aim to overcome this limitation by introducing a new framework for extracting semantically rich relations from text that involves three components. First, a semantic grammar structured around textual entities that distinguishes six motif classes: actions of an entity, treatments of an entity, agents acting upon an entity, patients acted upon by an entity, characterizations of an entity, and possessions of an entity; second, a comprehensive set of mapping rules, which make it possible to recover motifs from predictions of dependency parsers; third, an R package that allows researchers to extract motifs from their own texts. The framework is demonstrated in empirical analyses on gendered interaction in novels and constructions of collective identity by U.S. presidential candidates.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-13T03:12:42Z
      DOI: 10.1177/00491241221099551
       
  • The Additional Effects of Adaptive Survey Design Beyond Post-Survey
           Adjustment: An Experimental Evaluation

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      Authors: Shiyu Zhang, James Wagner
      Abstract: Sociological Methods & Research, Ahead of Print.
      Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the well-established post-survey adjustment. This paper reports the results of an experiment that evaluated the additional effect of adaptive design to post-survey adjustments. The experiment was conducted in the Detroit Metro Area Communities Study in 2021. We evaluated the adaptive design in five outcomes: 1) response rates, 2) demographic composition of respondents, 3) bias and variance of key survey estimates, 4) changes in significant results of regression models, and 5) costs. The most significant benefit of the adaptive design was its ability to generate more efficient survey estimates with smaller variances and smaller design effects.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-13T03:12:18Z
      DOI: 10.1177/00491241221099550
       
  • Promise Into Practice: Application of Computer Vision in Empirical
           Research on Social Distancing

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      Authors: Wim Bernasco, Evelien M. Hoeben, Dennis Koelma, Lasse Suonperä Liebst, Josephine Thomas, Joska Appelman, Cees G. M. Snoek, Marie Rosenkrantz Lindegaard
      Abstract: Sociological Methods & Research, Ahead of Print.
      Social scientists increasingly use video data, but large-scale analysis of its content is often constrained by scarce manual coding resources. Upscaling may be possible with the application of automated coding procedures, which are being developed in the field of computer vision. Here, we introduce computer vision to social scientists, review the state-of-the-art in relevant subfields, and provide a working example of how computer vision can be applied in empirical sociological work. Our application involves defining a ground truth by human coders, developing an algorithm for automated coding, testing the performance of the algorithm against the ground truth, and running the algorithm on a large-scale dataset of CCTV images. The working example concerns monitoring social distancing behavior in public space over more than a year of the COVID-19 pandemic. Finally, we discuss prospects for the use of computer vision in empirical social science research and address technical and ethical challenges.
      Citation: Sociological Methods & Research
      PubDate: 2022-05-09T03:35:10Z
      DOI: 10.1177/00491241221099554
       
  • Why Measurement Invariance is Important in Comparative Research. A
           Response to Welzel et al. (2021)

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      Authors: Bart Meuleman, Tomasz Żółtak, Artur Pokropek, Eldad Davidov, Bengt Muthén, Daniel L. Oberski, Jaak Billiet, Peter Schmidt
      Abstract: Sociological Methods & Research, Ahead of Print.
      Welzel et al. (2021) claim that non-invariance of instruments is inconclusive and inconsequential in the field for cross-cultural value measurement. In this response, we contend that several key arguments on which Welzel et al. (2021) base their critique of invariance testing are conceptually and statistically incorrect. First, Welzel et al. (2021) claim that value measurement follows a formative rather than reflective logic. Yet they do not provide sufficient theoretical arguments for this conceptualization, nor do they discuss the disadvantages of this approach for validation of instruments. Second, their claim that strong inter-item correlations cannot be retrieved when means are close to the endpoint of scales ignores the existence of factor-analytic approaches for ordered-categorical indicators. Third, Welzel et al. (2021) propose that rather than of relying on invariance tests, comparability can be assessed by studying the connection with theoretically related constructs. However, their proposal ignores that external validation through nomological linkages hinges on the assumption of comparability. By means of two examples, we illustrate that violating the assumptions of measurement invariance can distort conclusions substantially. Following the advice of Welzel et al. (2021) implies discarding a tool that has proven to be very useful for comparativists.
      Citation: Sociological Methods & Research
      PubDate: 2022-04-22T06:54:37Z
      DOI: 10.1177/00491241221091755
       
  • Against the Mainstream: On the Limitations of Non-Invariance Diagnostics:
           Response to Fischer et al. and Meulemann et al.

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      Authors: Christian Welzel, Stefan Kruse, Lennart Brunkert
      Abstract: Sociological Methods & Research, Ahead of Print.
      Our original 2021 SMR article “Non-Invariance' An Overstated Problem with Misconceived Causes” disputes the conclusiveness of non-invariance diagnostics in diverse cross-cultural settings. Our critique targets the increasingly fashionable use of Multi-Group Confirmatory Factor Analysis (MGCFA), especially in its mainstream version. We document—both by mathematical proof and an empirical illustration—that non-invariance is an arithmetic artifact of group mean disparity on closed-ended scales. Precisely this arti-factualness renders standard non-invariance markers inconclusive of measurement inequivalence under group-mean diversity. Using the Emancipative Values Index (EVI), OA-Section 3 of our original article demonstrates that such artifactual non-invariance is inconsequential for multi-item constructs’ cross-cultural performance in nomological terms, that is, explanatory power and predictive quality. Given these limitations of standard non-invariance diagnostics, we challenge the unquestioned authority of invariance tests as a tool of measurement validation. Our critique provoked two teams of authors to launch counter-critiques. We are grateful to the two comments because they give us a welcome opportunity to restate our position in greater clarity. Before addressing the comments one by one, we reformulate our key propositions more succinctly.
      Citation: Sociological Methods & Research
      PubDate: 2022-04-08T06:01:22Z
      DOI: 10.1177/00491241221091754
       
  • Image Clustering: An Unsupervised Approach to Categorize Visual Data in
           Social Science Research

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      Authors: Han Zhang, Yilang Peng
      Abstract: Sociological Methods & Research, Ahead of Print.
      Automated image analysis has received increasing attention in social scientific research, yet existing scholarship has mostly covered the application of supervised learning to classify images into predefined categories. This study focuses on the task of unsupervised image clustering, which aims to automatically discover categories from unlabelled image data. We first review the steps to perform image clustering and then focus on one key challenge in this task—finding intermediate representations of images. We present several methods of extracting intermediate image representations, including the bag-of-visual-words model, self-supervised learning, and transfer learning (in particular, feature extraction with pretrained models). We compare these methods using various visual datasets, including images related to protests in China from Weibo, images about climate change on Instagram, and profile images of the Russian Internet Research Agency on Twitter. In addition, we propose a systematic way to interpret and validate clustering solutions. Results show that transfer learning significantly outperforms the other methods. The dataset used in the pretrained model critically determines what categories the algorithms can discover.
      Citation: Sociological Methods & Research
      PubDate: 2022-04-07T12:35:21Z
      DOI: 10.1177/00491241221082603
       
  • Evidence of Validity Does not Rule out Systematic Bias: A Commentary on
           Nomological Noise and Cross-Cultural Invariance

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      Authors: Ronald Fischer, Johannes Alfons Karl, Johnny R. J. Fontaine, Ype H. Poortinga
      Abstract: Sociological Methods & Research, Ahead of Print.
      We comment on the argument by Welzel, Brunkert, Kruse and Inglehart (2021) that theoretically expected associations in nomological networks should take priority over invariance tests in cross-national research. We agree that narrow application of individual tools, such as multi-group confirmatory factor analysis with data that violates the assumptions of these techniques, can be misleading. However, findings that fit expectations of nomological networks may not be free of bias. We present supporting evidence of systematic bias affecting nomological network relationships from a) previous research on intelligence and response styles, b) two simulation studies, and c) data on the choice index from the World Value Survey (WVS). Our main point is that nomological network analysis by itself is insufficient to rule out systematic bias in data. We point out how a thoughtful exploration of sources of biases in cross-national data can contribute to stronger theory development.
      Citation: Sociological Methods & Research
      PubDate: 2022-04-06T03:21:25Z
      DOI: 10.1177/00491241221091756
       
  • Do Quantitative and Qualitative Research Reflect two Distinct
           Cultures' An Empirical Analysis of 180 Articles Suggests “no”

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      Authors: David Kuehn, Ingo Rohlfing
      Abstract: Sociological Methods & Research, Ahead of Print.
      The debate about the characteristics and advantages of quantitative and qualitative methods is decades old. In their seminal monograph, A Tale of Two Cultures (2012, ATTC), Gary Goertz and James Mahoney argue that methods and research design practices for causal inference can be distinguished as two cultures that systematically differ from each other along 25 specific characteristics. ATTC’s stated goal is a description of empirical patterns in quantitative and qualitative research. Yet, it does not include a systematic empirical evaluation as to whether the 25 are relevant and valid descriptors of applied research. In this paper, we derive five observable implications from ATTC and test the implications against a stratified random sample of 90 qualitative and 90 quantitative articles published in six journals between 1990–2012. Our analysis provides little support for the two-cultures hypothesis. Quantitative methods are largely implemented as described in ATTC, whereas qualitative methods are much more diverse than ATTC suggests. While some practices do indeed conform to the qualitative culture, many others are implemented in a manner that ATTC characterizes as constitutive of the quantitative culture. We find very little evidence for ATTC's anchoring of qualitative research with set-theoretic approaches to empirical social science research. The set-theoretic template only applies to a fraction of the qualitative research that we reviewed, with the majority of qualitative work incorporating different method choices.
      Citation: Sociological Methods & Research
      PubDate: 2022-04-01T06:36:15Z
      DOI: 10.1177/00491241221082597
       
  • Sequential On-Device Multitasking within Online Surveys: A Data Quality
           and Response Behavior Perspective

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      Authors: Jean Philippe Décieux
      Abstract: Sociological Methods & Research, Ahead of Print.
      The risk of multitasking is high in online surveys. However, knowledge on the effects of multitasking on answer quality is sparse and based on suboptimal approaches. Research reports inconclusive results concerning the consequences of multitasking on task performance. However, studies suggest that especially sequential-multitasking activities are expected to be critical. Therefore, this study focusses on sequential-on-device-multitasking activities (SODM) and its consequences for data quality. Based on probability-based data, this study aims to reveal the prevalence of SODM based on the javascript function OnBlur, to reflect the its determinants and to examine the consequences for data quality. Results show that SODM was detected for 25% of all respondents and that respondent attributes and the device used to answer the survey are related to SODM. Moreover, it becomes apparent that SODM is significantly correlated to data quality measures. Therefore, I propose SODM behavior as a new instrument for researching suboptimal response behavior.
      Citation: Sociological Methods & Research
      PubDate: 2022-03-07T04:36:24Z
      DOI: 10.1177/00491241221082593
       
  • Bounding Causes of Effects With Mediators

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      Authors: Philip Dawid, Macartan Humphreys, Monica Musio
      Abstract: Sociological Methods & Research, Ahead of Print.
      Suppose X and Y are binary exposure and outcome variables, and we have full knowledge of the distribution of Y, given application of X. We are interested in assessing whether an outcome in some case is due to the exposure. This “probability of causation” is of interest in comparative historical analysis where scholars use process tracing approaches to learn about causes of outcomes for single units by observing events along a causal path. The probability of causation is typically not identified, but bounds can be placed on it. Here, we provide a full characterization of the bounds that can be achieved in the ideal case that X and Y are connected by a causal chain of complete mediators, and we know the probabilistic structure of the full chain. Our results are largely negative. We show that, even in these very favorable conditions, the gains from positive evidence on mediators is modest.
      Citation: Sociological Methods & Research
      PubDate: 2022-03-03T09:08:07Z
      DOI: 10.1177/00491241211036161
       
  • Iteration in Mixed-Methods Research Designs Combining Experiments and
           Fieldwork,

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      Authors: Verónica Pérez Bentancur, Lucía Tiscornia
      Abstract: Sociological Methods & Research, Ahead of Print.
      Experimental designs in the social sciences have received increasing attention due to their power to produce causal inferences. Nevertheless, experimental research faces limitations, including limited external validity and unrealistic treatments. We propose combining qualitative fieldwork and experimental design iteratively—moving back-and-forth between elements of a research design—to overcome these limitations. To properly evaluate the strength of experiments researchers need information about the context, data, and previous knowledge used to design the treatment. To support our argument, we analyze 338 pre-analysis plans submitted to the Evidence in Governance and Politics repository in 2019 and the design of a study on public opinion support for punitive policing practices in Montevideo, Uruguay. The paper provides insights about using qualitative fieldwork to enhance the external validity, transparency and replicability of experimental research, and a practical guide for researchers who want to incorporate iteration to their research designs.
      Citation: Sociological Methods & Research
      PubDate: 2022-03-03T08:21:13Z
      DOI: 10.1177/00491241221082595
       
  • Social Encounters and the Worlds Beyond: Putting Situationalism to Work
           for Qualitative Interviews

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      Authors: Anders Vassenden, Marte Mangset
      Abstract: Sociological Methods & Research, Ahead of Print.
      In Goffman's terms, qualitative interviews are social encounters with their own realities. Hence, the ‘situational critique’ holds that interviews cannot produce knowledge about the world beyond these encounters, and that other methods, ethnography in particular, render lived life more accurately. The situational critique cannot be dismissed; yet interviewing remains an indispensable sociological tool. This paper demonstrates the value that situationalism holds for interviewing. We examine seemingly contradictory findings from interview studies of middle-class identity (cultural hierarchies and/or egalitarianism'). We then render these contradictions comprehensible by interpreting data excerpts through ‘methodological situationalism’: Goffman's theories of interaction order, ritual, and frontstage/backstage. In ‘situationalist interviewing,’ we suggest that sociologists be attentive to the ‘imagined audiences’ and ‘imagined communities’. These are key to identifying the situations, interaction orders, and cultural repertoires that lie beyond the interview encounter, but to which it refers. In sum, we argue for greater situational awareness among sociologists who must rely on interviews. We also discuss techniques and measures that can facilitate situational awareness. A promise of situational interviewing is that it helps us make sense of contradictions, ambiguities, and disagreements within and between interviews.
      Citation: Sociological Methods & Research
      PubDate: 2022-03-02T01:32:50Z
      DOI: 10.1177/00491241221082609
       
  • Abductive Coding: Theory Building and Qualitative (Re)Analysis

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      Authors: Luis Vila-Henninger, Claire Dupuy, Virginie Van Ingelgom, Mauro Caprioli, Ferdinand Teuber, Damien Pennetreau, Margherita Bussi, Cal Le Gall
      Abstract: Sociological Methods & Research, Ahead of Print.
      Qualitative secondary analysis has generated heated debate regarding the epistemology of qualitative research. We argue that shifting to an abductive approach provides a fruitful avenue for qualitative secondary analysts who are oriented towards theory-building. However, the concrete implementation of abduction remains underdeveloped—especially for coding. We address this key gap by outlining a set of tactics for abductive analysis that can be applied for qualitative analysis. Our approach applies Timmermans and Tavory's ( Timmermans and Tavory 2012; Tavory and Timmermans 2014) three stages of abduction in three steps for qualitative (secondary) analysis: Generating an Abductive Codebook, Abductive Data Reduction through Code Equations, and In-Depth Abductive Qualitative Analysis. A key contribution of our article is the development of “code equations”—defined as the combination of codes to operationalize phenomena that span individual codes. Code equations are an important resource for abduction and other qualitative approaches that leverage qualitative data to build theory.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-15T02:17:52Z
      DOI: 10.1177/00491241211067508
       
  • In Search of a Comparable Measure of Generalized Individual Religiosity in
           the World Values Survey

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      Authors: Alisa Remizova, Maksim Rudnev, Eldad Davidov
      Abstract: Sociological Methods & Research, Ahead of Print.
      Individual religiosity measures are used by researchers to describe and compare individuals and societies. However, the cross-cultural comparability of the measures has often been questioned but rarely empirically tested. In the current study, we examined the cross-national measurement invariance properties of generalized individual religiosity in the sixth wave of the World Values Survey. For the analysis, we used multiple group confirmatory factor analysis and alignment. Our results demonstrated that a theoretically driven measurement model was not invariant across all countries. We suggested four unidimensional measurement models and four overlapping groups of countries in which these measurement models demonstrated approximate invariance. The indicators that covered praying practices, importance of religion, and confidence in its institutions were more cross-nationally invariant than other indicators.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-09T04:19:09Z
      DOI: 10.1177/00491241221077239
       
  • Comparing Single- and Multiple-Question Designs of Measuring Family Income
           in China Family Panel Studies

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      Authors: Qiong Wu, Liping Gu
      Abstract: Sociological Methods & Research, Ahead of Print.
      Family income questions in general purpose surveys are usually collected with either a single-question summary design or a multiple-question disaggregation design. It is unclear how estimates from the two approaches agree with each other. The current paper takes advantage of a large-scale survey that has collected family income with both methods. With data from 14,222 urban and rural families in the 2018 wave of the nationally representative China Family Panel Studies, we compare the two estimates, and further evaluate factors that might contribute to the discrepancy. We find that the two estimates are loosely matched in only a third of all families, and most of the matched families have a simple income structure. Although the mean of the multiple-question estimate is larger than that of the single-question estimate, the pattern is not monotonic. At lower percentiles up till the median, the single-question estimate is larger, whereas the multiple-question estimate is larger at higher percentiles. Larger family sizes and more income sources contribute to higher likelihood of inconsistent estimates from the two designs. Families with wage income as the main income source have the highest likelihood of giving consistent estimates compared with all other families. In contrast, families with agricultural income or property income as the main source tend to have very high probability of larger single-question estimates. Omission of certain income components and rounding can explain over half of the inconsistencies with higher multiple-question estimates and a quarter of the inconsistencies with higher single-question estimates.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-08T11:26:36Z
      DOI: 10.1177/00491241221077238
       
  • Visual Design and Cognition in List-Style Open-Ended Questions in Web
           Probing

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      Authors: Katharina Meitinger, Tanja Kunz
      Abstract: Sociological Methods & Research, Ahead of Print.
      Previous research reveals that the visual design of open-ended questions should match the response task so that respondents can infer the expected response format. Based on a web survey including specific probes in a list-style open-ended question format, we experimentally tested the effects of varying numbers of answer boxes on several indicators of response quality. Our results showed that using multiple small answer boxes instead of one large box had a positive impact on the number and variety of themes mentioned, as well as on the conciseness of responses to specific probes. We found no effect on the relevance of themes and the risk of item non-response. Based on our findings, we recommend using multiple small answer boxes instead of one large box to convey the expected response format and improve response quality in specific probes. This study makes a valuable contribution to the field of web probing, extends the concept of response quality in list-style open-ended questions, and provides a deeper understanding of how visual design features affect cognitive response processes in web surveys.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-08T05:05:33Z
      DOI: 10.1177/00491241221077241
       
  • The Potential for Using a Shortened Version of the Everyday Discrimination
           Scale in Population Research with Young Adults: A Construct Validation
           Investigation

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      Authors: Aprile D. Benner, Shanting Chen, Celeste C. Fernandez, Mark D. Hayward
      Abstract: Sociological Methods & Research, Ahead of Print.
      Discrimination is associated with numerous psychological health outcomes over the life course. The nine-item Everyday Discrimination Scale (EDS) is one of the most widely used measures of discrimination; however, this nine-item measure may not be feasible in large-scale population health surveys where a shortened discrimination measure would be advantageous. The current study examined the construct validity of a combined two-item discrimination measure adapted from the EDS by Add Health (N = 14,839) as compared to the full nine-item EDS and a two-item EDS scale (parallel to the adapted combined measure) used in the National Survey of American Life (NSAL; N = 1,111) and National Latino and Asian American Study (NLAAS) studies (N = 1,055). Results identified convergence among the EDS scales, with high item-total correlations, convergent validity, and criterion validity for psychological outcomes, thus providing evidence for the construct validity of the two-item combined scale. Taken together, the findings provide support for using this reduced scale in studies where the full EDS scale is not available.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-07T05:48:20Z
      DOI: 10.1177/00491241211067512
       
  • Do Different Devices Perform Equally Well with Different Numbers of Scale
           Points and Response Formats' A test of measurement invariance and
           reliability

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      Authors: Natalja Menold, Vera Toepoel
      Abstract: Sociological Methods & Research, Ahead of Print.
      Research on mixed devices in web surveys is in its infancy. Using a randomized experiment, we investigated device effects (desktop PC, tablet and mobile phone) for six response formats and four different numbers of scale points. N = 5,077 members of an online access panel participated in the experiment. An exact test of measurement invariance and Composite Reliability were investigated. The results provided full data comparability for devices and formats, with the exception of continuous Visual Analog Scale (VAS), but limited comparability for different numbers of scale points. There were device effects on reliability when looking at the interactions with formats and number of scale points. VAS, use of mobile phones and five point scales consistently gained lower reliability. We suggest technically less demanding implementations as well as a unified design for mixed-device surveys.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-07T05:47:55Z
      DOI: 10.1177/00491241221077237
       
  • Moving Beyond Linear Regression: Implementing and Interpreting Quantile
           Regression Models With Fixed Effects

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      Authors: Fernando Rios-Avila, Michelle Lee Maroto
      Abstract: Sociological Methods & Research, Ahead of Print.
      Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR) often result in divergent findings that are not always well understood. In light of such discrepancies, this paper reviews how to implement and interpret a range of LR, CQR, and UQR models with fixed effects. It also discusses the use of Quantile Treatment Effect (QTE) models as an alternative to overcome some of the limitations of CQR and UQR models. We then review how to interpret results in the presence of fixed effects based on a replication of Budig and Hodges’s work on the motherhood penalty using NLSY79 data.
      Citation: Sociological Methods & Research
      PubDate: 2022-02-01T10:28:19Z
      DOI: 10.1177/00491241211036165
       
  • Updating a Time-Series of Survey Questions: The Case of Abortion Attitudes
           in the General Social Survey

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      Authors: Sarah K. Cowan, Michael Hout, Stuart Perrett
      Abstract: Sociological Methods & Research, Ahead of Print.
      Long-running surveys need a systematic way to reflect social change and to keep items relevant to respondents, especially when they ask about controversial subjects, or they threaten the items’ validity. We propose a protocol for updating measures that preserves content and construct validity. First, substantive experts articulate the current and anticipated future terms of debate. Then survey experts use this substantive input and their knowledge of existing measures to develop and pilot a large battery of new items. Third, researchers analyze the pilot data to select items for the survey of record. Finally, the items appear on the survey-of-record, available to the whole user community. Surveys-of-record have procedures for changing content that determine if the new items appear just once or become part of the core. We provide the example of developing new abortion attitude measures in the General Social Survey. Current questions ask whether abortion should be legal under varying circumstances. The new abortion items ask about morality, access, state policy, and interpersonal dynamics. They improve content and construct validity and add new insights into Americans’ abortion attitudes.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-27T02:43:11Z
      DOI: 10.1177/00491241211043140
       
  • Relevant, Irrelevant, or Ambiguous' Toward a New Interpretation of
           QCA’s Solution Types

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      Authors: Tim Haesebrouck
      Abstract: Sociological Methods & Research, Ahead of Print.
      The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA’s main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated way, in order to get as much information as possible on the causal structure behind the phenomenon under investigation. The parsimonious solution is capable of identifying causally relevant conditions, the conservative solution of identifying contextually irrelevant conditions. In addition to conditions for which the data provide evidence that they are causally relevant or contextually irrelevant, there will be conditions for which the data neither suggest that they are relevant nor contextually irrelevant. In line with the procedure for crafting the intermediate solution, it is possible to make clear for which of these ambiguous conditions it is not plausible that they are relevant in the context of the research.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-25T09:39:21Z
      DOI: 10.1177/00491241211036153
       
  • A New Approach to Detecting Cheating in Sensitive Surveys: The Cheating
           Detection Triangular Model

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      Authors: Julia Meisters, Adrian Hoffmann, Jochen Musch
      Abstract: Sociological Methods & Research, Ahead of Print.
      Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting instruction non-adherence, and similar to the Triangular Model, it uses simplified instructions to improve respondents’ understanding of the procedure. Based on a comparison with the known prevalence of a sensitive attribute serving as external criterion, we report the first individual-level validation of the Cheating Detection Model, the Triangular Model and the Cheating Detection Triangular Model. Moreover, the sensitivity and specificity of all models was assessed, as well as the respondents’ subjective evaluation of all questioning technique formats. Based on our results, the Cheating Detection Triangular Model appears to be the best choice among the investigated indirect questioning techniques.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-19T11:49:08Z
      DOI: 10.1177/00491241211055764
       
  • Self-protecting responses in randomized response designs: A survey on
           intimate partner violence during the coronavirus disease 2019 pandemic

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      Authors: Fabiola Reiber, Donna Bryce, Rolf Ulrich
      Abstract: Sociological Methods & Research, Ahead of Print.
      Randomized response techniques (RRTs) are applied to reduce response biases in self-report surveys on sensitive research questions (e.g., on socially undesirable characteristics). However, there is evidence that they cannot completely eliminate self-protecting response strategies. To address this problem, there are RRTs specifically designed to measure the extent of such strategies. Here we assessed the recently devised unrelated question model—cheating extension (UQMC) in a preregistered online survey on intimate partner violence (IPV) victimization and perpetration during the first contact restrictions as containment measures for the outbreak of the coronavirus disease 2019 pandemic in Germany in early 2020. The UQMC accounting for self-protecting responses described the data better than its predecessor model which assumes instruction adherence. The resulting three-month prevalence estimates were about 10% and we found a high proportion of self-protecting responses in the group of female participants queried about IPV victimization. However, unexpected results concerning the differences in prevalence estimates across the groups queried about victimization and perpetration highlight the difficulty of investigating sensitive research questions even using methods that guarantee anonymity and the importance of interpreting the respective estimates with caution.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-17T04:14:03Z
      DOI: 10.1177/00491241211043138
       
  • The Gap-Closing Estimand: A Causal Approach to Study Interventions That
           Close Disparities Across Social Categories

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      Authors: Ian Lundberg
      Abstract: Sociological Methods & Research, Ahead of Print.
      Disparities across race, gender, and class are important targets of descriptive research. But rather than only describe disparities, research would ideally inform interventions to close those gaps. The gap-closing estimand quantifies how much a gap (e.g., incomes by race) would close if we intervened to equalize a treatment (e.g., access to college). Drawing on causal decomposition analyses, this type of research question yields several benefits. First, gap-closing estimands place categories like race in a causal framework without making them play the role of the treatment (which is philosophically fraught for non-manipulable variables). Second, gap-closing estimands empower researchers to study disparities using new statistical and machine learning estimators designed for causal effects. Third, gap-closing estimands can directly inform policy: if we sampled from the population and actually changed treatment assignments, how much could we close gaps in outcomes' I provide open-source software (the R package gapclosing) to support these methods.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-13T08:55:12Z
      DOI: 10.1177/00491241211055769
       
  • Recurrent Multinomial Models for Categorical Sequences

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      Authors: Michael Schultz
      Abstract: Sociological Methods & Research, Ahead of Print.
      This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering recurrent patterns by employing a more restrictive Markov assumption. The resulting model, which I call the recurrent multinomial model, provides a parsimonious representation of recurrent sequences, enabling the investigation of recurrences on longer time scales than existing models. The utility of recurrent multinomial models is demonstrated by applying them to the case of conversational turn-taking in meetings of the Federal Open Market Committee (FOMC). Analyses are effectively able to discover norms around turn-reclaiming, participation, and suppression and to evaluate how these norms vary throughout the course of the meeting.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-11T10:47:10Z
      DOI: 10.1177/00491241211067513
       
  • Estimation and sensitivity analysis for causal decomposition in health
           disparity research

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      Authors: Soojin Park, Xu Qin, Chioun Lee
      Abstract: Sociological Methods & Research, Ahead of Print.
      In the field of disparities research, there has been growing interest in developing a counterfactual-based decomposition analysis to identify underlying mediating mechanisms that help reduce disparities in populations. Despite rapid development in the area, most prior studies have been limited to regression-based methods, undermining the possibility of addressing complex models with multiple mediators and/or heterogeneous effects. We propose a novel estimation method that effectively addresses complex models. Moreover, we develop a sensitivity analysis for possible violations of an identification assumption. The proposed method and sensitivity analysis are demonstrated with data from the Midlife Development in the US study to investigate the degree to which disparities in cardiovascular health at the intersection of race and gender would be reduced if the distributions of education and perceived discrimination were the same across intersectional groups.
      Citation: Sociological Methods & Research
      PubDate: 2022-01-11T03:56:06Z
      DOI: 10.1177/00491241211067516
       
  • And the Rest is History: Measuring the Scope and Recall of Wikipedia’s
           Coverage of Three Women’s Movement Subgroups

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      Authors: Laura K. Nelson, Rebekah Getman, Syed Arefinul Haque
      Abstract: Sociological Methods & Research, Ahead of Print.
      Narrating history is perpetually contested, shaping and reshaping how nations and people understand both their pasts and the current moment. Measuring and evaluating the scope of histories is methodologically challenging. In this paper we provide a general approach and a specific method to measure historical recall. Operationalizing historical information as one or more word phrases, we use the phrase-mining RAKE algorithm on a collection of primary historical documents to extract first-person historical evidence, and then measure recall via phrases present on contemporary Wikipedia, taken to represent a publicly-accessible summary of existing knowledge on virtually any historical topic. We demonstrate this method using women's movements in the United States as a case study of a debated historical field. We found that issues important to working-class elements of the movement were less likely to be covered on Wikipedia compared to other subsections of the movement. Combining this method with a qualitative analysis of select articles, we identified a typology of mechanisms leading to historical omissions: paucity, restrictive paradigms, and categorical narrowness. Our approach, we conclude, can be used to both evaluate the recall of a body of history and to actively intervene in enlarging the scope of our histories and historical knowledge.
      Citation: Sociological Methods & Research
      PubDate: 2021-12-30T01:29:33Z
      DOI: 10.1177/00491241211067514
       
  • A Joint Model for Longitudinal and Time-to-event Data in Social and Life
           Course Research: Employment Status and Time to Retirement

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      Authors: Jolien Cremers, Laust Hvas Mortensen, Claus Thorn Ekstrøm
      Abstract: Sociological Methods & Research, Ahead of Print.
      Longitudinal studies including a time-to-event outcome in social research often use a form of event history analysis to analyse the influence of time-varying endogenous covariates on the time-to-event outcome. Many standard event history models however assume the covariates of interest to be exogenous and inclusion of an endogenous covariate may lead to bias. Although such bias can be dealt with by using joint models for longitudinal and time-to-event outcomes, these types of models are underused in social research. In order to fill this gap in the social science modelling toolkit, we introduce a novel Bayesian joint model in which a multinomial longitudinal outcome is modelled simultaneously with a time-to-event outcome. The methodological novelty of this model is that it concerns a correlated random effects association structure that includes a multinomial longitudinal outcome. We show the use of the joint model on Danish labour market data and compare the joint model to a standard event history model. The joint model has three advantages over a standard survival model. It decreases bias, allows us to explore the relation between exogenous covariates and the longitudinal outcome and can be flexibly extended with multiple time-to-event and longitudinal outcomes.
      Citation: Sociological Methods & Research
      PubDate: 2021-12-14T12:34:10Z
      DOI: 10.1177/00491241211055770
       
  • An Empirical Comparison of Four Generalized Trust Scales: Test–Retest
           Reliability, Measurement Invariance, Predictive Validity, and
           Replicability

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      Authors: Blaine G. Robbins
      Abstract: Sociological Methods & Research, Ahead of Print.
      The Stranger Face Trust scale (SFT) and Imaginary Stranger Trust scale (IST) are two new self-report measures of generalized trust that assess trust in strangers—both real and imaginary—across four trust domains. Prior research has established the reliability and validity of SFT and IST, but a number of measurement validation tests remain. Across three separate studies, I assess the test–retest reliability, measurement invariance, predictive validity, and replicability of SFT and IST, with the misanthropy scale (MST) and generalized social trust scale (GST) serving as benchmarks. First, tests of internal consistency, test–retest reliability, and longitudinal measurement invariance established that all four generalized trust scales were acceptably reliable, with SFT and IST yielding greater overall reliability than MST and GST. Second, tests of multiple group measurement invariance revealed that SFT and IST were equivalent across gender, race, education, and age groups, while MST and GST were non-equivalent across the same sociodemographic groups. Third, an investment game established the predictive validity of SFT and MST, with IST and GST yielding poor predictive validity. Fourth, tests of factor structure and measurement invariance indicated that all four generalized trust scales replicated across samples. The present findings bolster the validity, reliability, and measurement equivalence of SFT and IST, while illustrating the compromised validity and measurement non-equivalence of MST and GST. Implications for the measurement of generalized trust are discussed.
      Citation: Sociological Methods & Research
      PubDate: 2021-12-09T06:02:52Z
      DOI: 10.1177/00491241211055765
       
  • Analyzing factorial survey data with structural equation models

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      Authors: Bert Weijters, Eldad Davidov, Hans Baumgartner
      Abstract: Sociological Methods & Research, Ahead of Print.
      In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.
      Citation: Sociological Methods & Research
      PubDate: 2021-11-29T01:07:26Z
      DOI: 10.1177/00491241211043139
       
  • A Rolling Panel Model of Cohort, Period, and Aging Effects for the
           Analysis of the General Social Survey

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      Authors: Stephen L. Morgan, Jiwon Lee
      Abstract: Sociological Methods & Research, Ahead of Print.
      The linear dependence of age, period, and birth cohort is a challenge for the analysis of social change. With either repeated cross-sectional data or conventional panel data, raw change cannot be decomposed into over-time differences that are attributable to the effects of common experiences of alternative birth cohorts, features of the periods under observation, and the cumulation of lifecourse aging. This article proposes a rolling panel model for cohort, period, and aging effects, suggested by and tuned to the treble panel data collected for the General Social Survey from 2006 through 2014. While the model does not offer a general solution for the identification of the classical age-period-cohort accounting model, it yields warranted interpretations under plausible assumptions that are reasonable for many outcomes of interest. In particular, if aging effects can be assumed to be invariant over the course of an observation interval, and if separate panel samples of the full age distribution overlap within the same observation interval, then period and aging effects can be parameterized and interpreted separately, adjusted for cohort differences that pulse through the same observation interval. The estimated cohort effects during the observation interval are then interpretable as effects during the observation interval of entangled period and cumulated aging differences from before the observation interval.
      Citation: Sociological Methods & Research
      PubDate: 2021-11-29T01:05:50Z
      DOI: 10.1177/00491241211043135
       
  • Using Inverse Probability Weighting to Address Post-Outcome Collider Bias

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      Authors: Richard Breen, John Ermisch
      Abstract: Sociological Methods & Research, Ahead of Print.
      We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds of post-outcome confounding, and we show the specific situations in which inverse probability weighting will allow us to obtain estimates that are consistent or, if not consistent, less biased than those obtained via ordinary least squares regression.
      Citation: Sociological Methods & Research
      PubDate: 2021-11-17T12:56:51Z
      DOI: 10.1177/00491241211043131
       
  • Method Bias Mechanisms and Procedural Remedies

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      Authors: Minghui Yao, Yunjie (Calvin) Xu
      Abstract: Sociological Methods & Research, Ahead of Print.
      As a crucial method in organizational and social behavior research, self-report surveys must manage method bias. Method biases are distorted scores in survey response, distorted variance in variables, and distorted relational estimates between variables caused by method designs. Studies on method bias have focused on post hoc statistical control, but integrated analyses of the sociopsychological mechanism of method bias are lacking. This review proposes a framework for method bias and offers a relatively complete and detailed review of the sociopsychological and statistical mechanisms of four main types of method bias and their procedural remedies. This review proposes “reduce, remove, and rectify” as a guideline for researchers in survey design to address method bias. Finally, this review presents two directions for future methodology research.
      Citation: Sociological Methods & Research
      PubDate: 2021-11-10T06:12:17Z
      DOI: 10.1177/00491241211043141
       
  • Measuring the Nature of Individual Sequences

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      Authors: Gilbert Ritschard
      Abstract: Sociological Methods & Research, Ahead of Print.
      This study reviews and compares indicators that can serve to characterize numerically the nature of state sequences. It also introduces several new indicators. Alongside basic measures such as the length, the number of visited distinct states, and the number of state changes, we shall consider composite measures such as turbulence and the complexity index, and measures that take account of the nature (e.g., positive vs. negative or ranking) of the states. The discussion points out the strange behavior of some of the measures—Elzinga’s turbulence and the precarity index of Ritschard, Bussi, and O’Reilly in particular—and propositions are made to avoid these flaws. The usage of the indicators is illustrated with two applications using data from the Swiss Household Panel. The first application tests the U-shape hypothesis about the evolution of life satisfaction along the life course, and the second one examines the scarring effect of earlier employment sequences.
      Citation: Sociological Methods & Research
      PubDate: 2021-09-28T03:30:57Z
      DOI: 10.1177/00491241211036156
       
  • Coping With Plenitude: A Computational Approach to Selecting the Right
           Algorithm

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      Authors: Ramina Sotoudeh, Paul DiMaggio
      Abstract: Sociological Methods & Research, Ahead of Print.
      Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which method will perform best on never-before-seen empirical data sets. We apply this strategy to a class of methods that group respondents to attitude surveys according to whether they share construals of a given domain. This allows us to identify the relative strengths and weaknesses of the methods we consider, including relational class analysis, correlational class analysis, and eight other such variants. Results support the “no free lunch” view that researchers should abandon the quest for one best algorithm in favor of matching algorithms to kinds of data for which each is most appropriate and provide direction on how to do so.
      Citation: Sociological Methods & Research
      PubDate: 2021-09-13T08:48:14Z
      DOI: 10.1177/00491241211031273
       
  • A Robustness Test Protocol for Applied QCA: Theory and R Software
           Application

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      Authors: Ioana-Elena Oana, Carsten Q. Schneider
      Abstract: Sociological Methods & Research, Ahead of Print.
      The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency thresholds should all be tested. Second, we introduce the notion of “sensitivity range” as the range of values for any of these parameters within which the solution formula remains unchanged. Third, we argue that interpreting robustness is more intricate than simply checking if solutions remain unchanged. Beyond sensitivity ranges, researchers should assess robustness by evaluating changes in parameters of fit and the classification of cases as robust, shaky, or possible. Fourth, we enable researchers to perform more than one robustness test at a time by proposing the notions of a “test set”: the overlap between conceptually plausible alternative solutions that can be generated; and of a “robust core”: that part of a QCA solution that withstands the robustness checks. Fifth, we present functionalities implemented in the R package SetMethods that enable researchers to put in practice our proposals. These advancements are integrated into a comprehensive QCA Robustness Test Protocol consisting of three main tests: sensitivity ranges, fit-oriented robustness, and case-oriented robustness. We illustrate the protocol’s implementation with an example on high life expectancy across the globe.
      Citation: Sociological Methods & Research
      PubDate: 2021-08-26T08:50:55Z
      DOI: 10.1177/00491241211036158
       
  • A Tale of Twin Dependence: A New Multivariate Regression Model and an FGLS
           Estimator for Analyzing Outcomes With Network Dependence

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      Authors: Weihua An
      Abstract: Sociological Methods & Research, Ahead of Print.
      In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be additionally correlated based on patterned connections in the dependence network (e.g., according to whether the ties are asymmetric, mutual, or triadic). For example, when predicting a group of students’ smoking status, the outcome can depend on the students’ positions in their friendship network and also be correlated among friends. I show that analyses ignoring the mean dependence can lead to severe bias in the estimated coefficients while analyses ignoring the error dependence can lead to inefficient inferences and failures in recognizing unmeasured social processes. I compare the new model with related models such as multilevel models, spatial regression models, and exponential random graph models and show their connections and differences. I propose a two-step, feasible generalized least squares estimator to estimate the model that is computationally fast and robust. Simulations show the validity of the new model (and the estimator) while four empirical examples demonstrate its versatility. Associated R package “fglsnet” is available for public use.
      Citation: Sociological Methods & Research
      PubDate: 2021-08-12T09:38:31Z
      DOI: 10.1177/00491241211031263
       
  • The Social Autopsy

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      Authors: Stefan Timmermans, Pamela J. Prickett
      Abstract: Sociological Methods & Research, Ahead of Print.
      The social autopsy takes the death of a set of individuals as its starting point and then critically and systematically examines social and political conditions to explain these deaths and generate awareness and policy change. After distinguishing the social autopsy from other means to explain excess and premature deaths, we delineate three core methodological principles of the social autopsy: social relevance as a guiding criterion to sample the deaths to be autopsied, embedding the patterning of deaths in social worlds, and a focus on contextual causality and social mechanisms. We provide three contemporary examples of excess deaths calling out for social autopsies: school shootings, Black deaths at the hands of police, and migrant border deaths.
      Citation: Sociological Methods & Research
      PubDate: 2021-08-09T08:18:59Z
      DOI: 10.1177/00491241211036163
       
  • Path Analysis for Binary Random Variables

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      Authors: Martina Raggi, Elena Stanghellini, Marco Doretti
      Abstract: Sociological Methods & Research, Ahead of Print.
      The decomposition of the overall effect of a treatment into direct and indirect effects is here investigated with reference to a recursive system of binary random variables. We show how, for the single mediator context, the marginal effect measured on the log odds scale can be written as the sum of the indirect and direct effects plus a residual term that vanishes under some specific conditions. We then extend our definitions to situations involving multiple mediators and address research questions concerning the decomposition of the total effect when some mediators on the pathway from the treatment to the outcome are marginalized over. Connections to the counterfactual definitions of the effects are also made. Data coming from an encouragement design on students’ attitude to visit museums in Florence, Italy, are reanalyzed. The estimates of the defined quantities are reported together with their standard errors to compute p values and form confidence intervals.
      Citation: Sociological Methods & Research
      PubDate: 2021-08-03T09:04:22Z
      DOI: 10.1177/00491241211031260
       
  • Applying Responsive Survey Design to Small-Scale Surveys: Campus Surveys
           of Sexual Misconduct

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      Authors: William G. Axinn, James Wagner, Mick Couper, Scott Crawford
      Abstract: Sociological Methods & Research, Ahead of Print.
      Responsive survey design is a technique aimed at improving the efficiency or quality of surveys by using incoming data from the field to make design changes. The technique was pioneered on large national surveys, but the tools can also be applied on the smaller-scale surveys most commonly used by sociologists. We demonstrate responsive survey design in a small-scale, list-based sample survey of students on the topic of sexual misconduct. We investigate the impact of individual incentive levels and a two-phase responsive design with changes to mode of contact as approaches for limiting the potential of nonresponse bias in data from such surveys. Our analyses demonstrate that a two-phase design introducing telephone and face-to-face reminders to complete the survey can produce stronger change in response rates and characteristics of those who respond than higher incentive levels. These findings offer tools for sociologists designing smaller-scale surveys of special populations or sensitive topics.
      Citation: Sociological Methods & Research
      PubDate: 2021-07-30T08:53:18Z
      DOI: 10.1177/00491241211031270
       
  • Uncertainty, Possibility, and Causal Power in QCA

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      Authors: Roel Rutten
      Abstract: Sociological Methods & Research, Ahead of Print.
      Uncertainty undermines causal claims; however, the nature of causal claims decides what counts as relevant uncertainty. Empirical robustness is imperative in regularity theories of causality. Regularity theory features strongly in QCA, making its case sensitivity a weakness. Following qualitative comparative analysis (QCA) founder Charles Ragin’s emphasis on ontological realism, this article suggests causality as a power and thus breaks with the ontological determinism of regularity theories. Exercising causal powers makes it possible for human agents to achieve an outcome but does not determine that they will. The article explains how QCA’s truth table analysis “models” possibilistic uncertainty and how crisp sets do this better than fuzzy sets. Causal power is at the heart of critical realist philosophy of science. Like Ragin, critical realism suggests empirical analysis as merely describing underlying causal relationships. Empirical statements must be substantively interpreted into causal claims. The article is critical of “empiricist” QCA that infers causality from the robustness of set relationships.
      Citation: Sociological Methods & Research
      PubDate: 2021-07-27T09:59:27Z
      DOI: 10.1177/00491241211031268
       
  • Open-ended versus Closed Probes: Assessing Different Formats of Web
           Probing

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      Authors: Cornelia E. Neuert, Katharina Meitinger, Dorothée Behr
      Abstract: Sociological Methods & Research, Ahead of Print.
      The method of web probing integrates cognitive interviewing techniques into web surveys and is increasingly used to evaluate survey questions. In a usual web probing scenario, probes are administered immediately after the question to be tested (concurrent probing), typically as open-ended questions. A second possibility of administering probes is in a closed format, whereby the response categories for the closed probes are developed during previously conducted qualitative cognitive interviews. Using closed probes has several benefits, such as reduced costs and time efficiency, because this method does not require manual coding of open-ended responses. In this article, we investigate whether the insights gained into item functioning when implementing closed probes are comparable to the insights gained when asking open-ended probes and whether closed probes are equally suitable to capture the cognitive processes for which traditionally open-ended probes are intended. The findings reveal statistically significant differences with regard to the variety of themes, the patterns of interpretation, the number of themes per respondent, and nonresponse. No differences in number of themes across formats by sex and educational level were found.
      Citation: Sociological Methods & Research
      PubDate: 2021-07-21T09:01:51Z
      DOI: 10.1177/00491241211031271
       
  • Are National Family Surveys Biased toward the Happy Family' A
           Multiactor Analysis of Selective Survey Nonresponse

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      Authors: Matthijs Kalmijn
      Abstract: Sociological Methods & Research, Ahead of Print.
      Virtually, all large-scale family surveys in the United States and Europe have yielded a positive view of family ties in contemporary societies. The present study examines whether surveys like these are affected by selective nonresponse. Are people with negative family ties less likely to participate in surveys, and if so, to what extent does this yield a biased descriptive view of family solidarity' Using a novel multiactor design with matched register data, we examine the determinants of nonresponse of the parents of adult children aged 25–45 in the Netherlands. Our analysis reveals significant effects of the strength of parent–child ties on parental nonresponse, especially for fathers. Moreover, we find negative effects of divorce on father’s participation and this effect is stronger when family ties are weak. While these findings support the hypothesis of selective nonresponse, the magnitude of the effects is small and descriptive findings on family ties change only modestly when correcting for selective nonresponse.
      Citation: Sociological Methods & Research
      PubDate: 2021-07-02T09:00:58Z
      DOI: 10.1177/0049124120986208
       
  • Optimizing Consistency and Coverage in Configurational Causal Modeling

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      Authors: Michael Baumgartner, Mathias Ambühl
      Abstract: Sociological Methods & Research, Ahead of Print.
      Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the optimally obtainable consistency and coverage scores for data [math], so far, is a matter of repeatedly applying CCMs to [math] while varying threshold settings. This article introduces a procedure called ConCovOpt that calculates, prior to actual CCM analyses, the consistency and coverage scores that can optimally be obtained by models inferred from [math]. Moreover, we show how models reaching optimal scores can be methodically built in case of crisp-set and multi-value data. ConCovOpt is a tool, not for blindly maximizing model fit, but for rendering transparent the space of viable models at optimal fit scores in order to facilitate informed model selection—which, as we demonstrate by various data examples, may have substantive modeling implications.
      Citation: Sociological Methods & Research
      PubDate: 2021-06-03T08:57:17Z
      DOI: 10.1177/0049124121995554
       
  • A Theory of Higher Order Interactions Between Sensitive Variables:
           Empirical Evidences and an Application to a Variety of Smoking

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      Authors: Oluwaseun L. Olanipekun, JuLong Zhao, Rongdong Wang, Stephen A.Sedory, Sarjinder Singh
      Abstract: Sociological Methods & Research, Ahead of Print.
      In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing sensitive characteristics. However, there is a paucity of research studies that have addressed higher order interactions between these sensitive characters. In this article, we develop a new theory based on three proposed randomized response models which we name as: simple model, semi-crossed model, and fully crossed model. Twenty-one new unbiased estimators of seven parameters are introduced, their variance expressions are derived, and unbiased estimators of variances are developed. The three models are compared under various values of the parameters by computing the percent relative efficiency of one model over another model. The most efficient model is then applied to study the population proportions of three varieties of smoking habits among students, and their first- and second-order interactions. The last four sections (Ninth to Twelfth) are verifications of theoretical results using the Cramer–Rao lower bounds of variances for the developed 21 new estimators in randomized response sampling.
      Citation: Sociological Methods & Research
      PubDate: 2021-05-20T08:53:03Z
      DOI: 10.1177/0049124120986203
       
  • Robustness and Model Selection in Configurational Causal Modeling

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      Authors: Veli-Pekka Parkkinen, Michael Baumgartner
      Abstract: Sociological Methods & Research, Ahead of Print.
      In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal structures, rendering it impossible to determine exactly how they influence the correctness of selected models. This article develops a computable criterion of fit-robustness, which quantifies the degree to which a CCM model agrees with other models inferred from the same data under systematically varied threshold settings of fit parameters. Based on two extended series of inverse search trials on data simulated from known causal structures, the article moreover provides a precise assessment of the degree to which fit-robustness scoring is conducive to finding a correct causal model and how it compares to other approaches of model selection.
      Citation: Sociological Methods & Research
      PubDate: 2021-05-20T08:51:56Z
      DOI: 10.1177/0049124120986200
       
  • Surprising Causes: Propensity-adjusted Treatment Scores for Multimethod
           Case Selection

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      Authors: Daniel J. Galvin, Jason N. Seawright
      Abstract: Sociological Methods & Research, Ahead of Print.
      Scholarship on multimethod case selection in the social sciences has developed rapidly in recent years, but many possibilities remain unexplored. This essay introduces an attractive and advantageous new alternative, involving the selection of extreme cases on the treatment variable, net of the statistical influence of the set of known control variables. Cases that are extreme in this way are those in which the value of the main causal variable is as surprising as possible, and thus, this approach can be referred to as seeking “surprising causes.” There are practical advantages to selecting on surprising causes, and there are also advantages in terms of statistical efficiency in facilitating case-study discovery. We first argue for these advantages in general terms and then demonstrate them in an application regarding the dynamics of U.S. labor legislation.
      Citation: Sociological Methods & Research
      PubDate: 2021-05-19T08:57:27Z
      DOI: 10.1177/00491241211004632
       
  • A Meta-analysis of Studies on the Performance of the Crosswise Model

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      Authors: Rainer Schnell, Kathrin Thomas
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article provides a meta-analysis of studies using the crosswise model (CM) in estimating the prevalence of sensitive characteristics in different samples and populations. On a data set of 141 items published in 33 either articles or books, we compare the difference (Δ) between estimates based on the CM and a direct question (DQ). The overall effect size of Δ is 4.88; 95% CI [4.56, 5.21]. The results of a meta-regression indicate that Δ is smaller when general populations and nonprobability samples are considered. The population effect suggests an education effect: Differences between the CM and DQ estimates are more likely to occur when highly educated populations, such as students, are studied. Our findings raise concerns to what extent the CM is able to improve estimates of sensitive behavior in general population samples.
      Citation: Sociological Methods & Research
      PubDate: 2021-05-07T08:58:27Z
      DOI: 10.1177/0049124121995520
       
  • An Improved Two-stage Randomized Response Model for Estimating the
           Proportion of Sensitive Attribute

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      Authors: Ghulam Narjis, Javid Shabbir
      Abstract: Sociological Methods & Research, Ahead of Print.
      The randomized response technique (RRT) is an effective method designed to obtain the stigmatized information from respondents while assuring the privacy. In this study, we propose a new two-stage RRT model to estimate the prevalence of sensitive attribute ([math]). A simulation study shows that the empirical mean and variance of proposed estimator are close to corresponding theoretical values. The utility of proposed two-stage RRT model under stratification is also explored. An efficiency comparison between proposed two-stage RRT model and some existing RRT models is carried out numerically under simple and stratified random sampling.
      Citation: Sociological Methods & Research
      PubDate: 2021-05-05T09:29:51Z
      DOI: 10.1177/00491241211009950
       
  • Marginal and Conditional Confounding Using Logits

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      Authors: Kristian Bernt Karlson, Frank Popham, Anders Holm
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of confounding (marginal and conditional) that can be recovered from a simple standardization approach. We investigate when marginal and conditional confounding may differ, outline why the method by Karlson, Holm, and Breen recovers conditional confounding under a “no interaction”-assumption, and suggest that researchers may measure marginal confounding by using inverse probability weighting. We provide two empirical examples that illustrate our standardization approach.
      Citation: Sociological Methods & Research
      PubDate: 2021-04-09T07:14:43Z
      DOI: 10.1177/0049124121995548
       
  • Response Behavior and Quality of Survey Data: Comparing Elderly
           Respondents in Institutions and Private Households

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      Authors: Jan-Lucas Schanze
      Abstract: Sociological Methods & Research, Ahead of Print.
      An increasing age of respondents and cognitive impairment are usual suspects for increasing difficulties in survey interviews and a decreasing data quality. This is why survey researchers tend to label residents in retirement and nursing homes as hard-to-interview and exclude them from most social surveys. In this article, I examine to what extent this label is justified and whether quality of data collected among residents in institutions for the elderly really differs from data collected within private households. For this purpose, I analyze the response behavior and quality indicators in three waves of Survey of Health, Ageing and Retirement in Europe. To control for confounding variables, I use propensity score matching to identify respondents in private households who share similar characteristics with institutionalized residents. My results confirm that most indicators of response behavior and data quality are worse in institutions compared to private households. However, when controlling for sociodemographic and health-related variables, differences get very small. These results suggest the importance of health for the data quality irrespective of the housing situation.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-25T08:52:28Z
      DOI: 10.1177/0049124121995534
       
  • Non-invariance' An Overstated Problem With Misconceived Causes

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      Authors: Christian Welzel, Lennart Brunkert, Stefan Kruse, Ronald F. Inglehart
      Abstract: Sociological Methods & Research, Ahead of Print.
      Scholars study representative international surveys to understand cross-cultural differences in mentality patterns, which are measured via complex multi-item constructs. Methodologists in this field insist with increasing vigor that detecting “non-invariance” in how a construct’s items associate with each other in different national samples is an infallible sign of encultured in-equivalences in how respondents understand the items. Questioning this claim, we demonstrate that a main source of non-invariance is the arithmetic of closed-ended scales in the presence of sample mean disparity. Since arithmetic principles are culture-unspecific, the non-invariance that these principles enforce in statistical terms is inconclusive of encultured in-equivalences in semantic terms. Because of this inconclusiveness, our evidence reveals furthermore that non-invariance is inconsequential for the cross-cultural functioning of multi-item constructs as concerns their nomological linkages to other variables of interest. We discuss the implications of these insights for measurement validation in cross-cultural settings with large sample mean disparity.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-24T08:56:34Z
      DOI: 10.1177/0049124121995521
       
  • How bad could it be' Worst-case bounds on bias in multistate models
           due to unobserved transitions

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      Authors: Christian Dudel, Daniel C. Schneider
      Abstract: Sociological Methods & Research, Ahead of Print.
      Multistate models are often used in social research to analyze how individuals move between states. A typical application is the estimation of the lifetime spent in a certain state, like the lifetime spent in employment, or the lifetime spent in good health. Unfortunately, the estimation of such quantities is prone to several biases. In this paper, we study the bias due to the often implicitly used assumption that there are no unobserved transitions between states. This assumption does often not hold for the panel data typically used to estimate multistate models, as the states occupied by individuals are only known at specific points in time, and further transitions between panel waves are not recorded. We present partially identified estimates of the lifetime spent in a state, or worse-case bounds, which show the maximum possible level of bias due to unobserved transitions. We provide two examples studying the lifetime spent in disability (disabled life expectancy; DLE). The first example applies our methods to results on cohort trends in DLE in the U.S. taken from Crimmins et al. (2009). In the second example, we replicate findings from Mehta and Myrskylä (2017), and apply our methods to data from the U.S. Health and Retirement Study (HRS) in order to estimate the effects of health behaviors on DLE.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-18T09:02:00Z
      DOI: 10.1177/0049124121995540
       
  • Using Interviews to Understand Why: Challenges and Strategies in the Study
           of Motivated Action

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      Authors: Mario L. Small, Jenna M. Cook
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article examines an important and thorny problem in interview research: How to assess whether what people say motivated their actions actually did so' We ask three questions: What specific challenges are at play' How have researchers addressed them' And how should those strategies be evaluated' We argue that such research faces at least five challenges—deception, recall error, reasonableness bias, intentionality bias, and single-motive bias—that more than a dozen strategies have been deployed to address them; that the strategies have been external, internal, or interactional in nature; and that each class of strategies demands distinct evaluation criteria. Researchers will likely fail to uncover motivation if they ignore the possibility of each challenge, conflate one challenge with another, or deploy strategies unmatched to the challenge at hand. Our work helps systematize the evaluation of interview-based studies of motivated action and strengthen the scientific foundations of in-depth interview research.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-17T09:10:40Z
      DOI: 10.1177/0049124121995552
       
  • What Do We Mean By a “Hard-to-reach” Population' Legitimacy Versus
           Precarity as Barriers to Access

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      Authors: Rachel Ellis
      Abstract: Sociological Methods & Research, Ahead of Print.
      Numerous articles and textbooks advise qualitative researchers on accessing “hard-to-reach” or “hidden” populations. In this article, I compare two studies that I conducted with justice-involved women in the United States: a yearlong ethnography inside a state women’s prison and an interview study with formerly incarcerated women. Although these two populations are interconnected—and both are widely deemed hard-to-reach—the barriers to access differed. In the prison study, hard-to-reach reflected an issue of institutional legitimacy, in which researchers must demonstrate themselves and their proposed study as legible, appropriate, and worthy to organizational gatekeepers. In the reentry study, hard-to-reach reflected an issue of structural precarity, in which researchers must navigate the everyday vulnerabilities of research participants’ social position to ensure the study is inclusive and feasible. Juxtaposing these two experiences, I propose greater nuance to the term hard-to-reach such that researchers may proactively address institutional and structural barriers to access.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-09T09:32:10Z
      DOI: 10.1177/0049124121995536
       
  • Multiple Group Comparisons of the Fixed and Random Effects From the
           Generalized Linear Mixed Model

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      Authors: Daniel Kasper, Katrin Schulz-Heidorf, Knut Schwippert
      Abstract: Sociological Methods & Research, Ahead of Print.
      In this article, we extend Liao’s test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be applied when the fixed and random effects are multivariate normally distributed, and it works well for any link function and conditional distribution of the dependent variable of the GLMM. We also derived the asymptotic properties of this test, and because power information does not exist for either our new test statistic or Liao’s test, we implemented a power study to demonstrate the superiority of these tests over the alternatively proposed F test. Using an example, we show the application of the test and then discuss its possible restrictions with respect to the distribution of the random effects.
      Citation: Sociological Methods & Research
      PubDate: 2021-03-01T12:03:29Z
      DOI: 10.1177/0049124120986182
       
  • The Problem of Scaling in Exponential Random Graph Models

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      Authors: Scott W. Duxbury
      Abstract: Sociological Methods & Research, Ahead of Print.
      This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model—even those uncorrelated with other predictors—or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot be interpreted as effect sizes or compared between models and homophily coefficients, as well as other interaction coefficients, cannot be interpreted as substantive effects in most ERGM applications. We conduct a series of simulations considering the substantive impact of these issues, revealing that realistic levels of residual variation can have large consequences for ERGM inference. A flexible methodological framework is introduced to overcome these problems. Formal tests of mediation and moderation are also proposed. These methods are applied to revisit the relationship between selective mixing and triadic closure in a large AddHealth school friendship network. Extensions to other classes of statistical work models are discussed.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-23T09:40:58Z
      DOI: 10.1177/0049124120986178
       
  • How (Not) to Control for Population Size in Ecological Analyses

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      Authors: Benjamin Rohr, John Levi Martin
      Abstract: Sociological Methods & Research, Ahead of Print.
      It is common for social scientists to use formal quantitative methods to compare ecological units such as towns, schools, or nations. In many cases, the size of these units in terms of the number of individuals subsumed in each differs substantially. When the variables in question are counts, there is generally some attempt to neutralize differences in size by turning variables into ratios or by controlling for size. But methods that are appropriate in many demographic and epidemiological contexts have been used in settings where they may not be justified and may well introduce spurious relations between variables. We suggest local regressions as a simple diagnostic and generalized additive models as a superior modeling strategy, with double-residualized regressions as a backup for certain cases.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-22T09:21:23Z
      DOI: 10.1177/0049124120986188
       
  • Participant Observation, Observant Participation, and Hybrid Ethnography

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      Authors: Josh Seim
      Abstract: Sociological Methods & Research, Ahead of Print.
      How much should ethnographers involve themselves with the people, places, and processes they study' One answer has become increasingly popular: invert the standard method of participant observation into observant participation. This article draws on an ethnography of ambulance work to consider the trade-offs between these approaches. My fieldwork included “ride-alongs” with labor and management at a private ambulance firm in California (participant observation) and short-term employment as a novice emergency medical technician at the same company (observant participation). Beyond a simplistic distinction in “empirical depth,” I identify three issues at stake between participant observation and observant participation: field positioning, analytic gaze, and data assembly. Where participant observation presents more opportunities for mobile positioning, outward gazing, and inscription, observant participation presents more opportunities for fixed positioning, inward gazing, and incarnation. In addition to justifying such contrasts, I consider the advantages of mixing these styles into a hybrid approach when feasible.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-10T09:34:10Z
      DOI: 10.1177/0049124120986209
       
  • Theory Building, Case Dependence, and Researchers’ Bounded Rationality:
           An Illustration From Studies of Innovation Diffusion

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      Authors: Nuno Oliveira, Davide Secchi
      Abstract: Sociological Methods & Research, Ahead of Print.
      Researchers increasingly take advantage of the comparative case design to build theory, but the degree of case dependence is occasionally discussed and theorized. We suggest that the comparative case study design might be subject to an often underappreciated threat—dependence across cases—under certain conditions. Using research on innovation diffusion as an illustration, we explore the role of social linkages across cases when building theory through comparison and contrast between cases. We develop an agent-based simulation, grounded by comparative case research about innovation diffusion, as novel way to study the implications of case dependence in theory building using multiple-case study research. Our simulation results suggest that the degree of case dependence has a nontrivial bearing on innovation diffusion experienced by case entities, specifically when the researcher draws a few case entities operating in a highly interconnected industry. Under these conditions, overlooking the degree of case dependence might weaken newly built theory against commonly held standards of internal validity and external validity in inductive research. We conceptualize the issue of case dependence as a concern about researchers’ bounded rationality. Accordingly, we build on our findings to provide actionable advice aiming to alleviate this concern while being amendable to the variety of approaches to build theory from multiple cases in social sciences.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-09T09:44:12Z
      DOI: 10.1177/0049124120986201
       
  • Taking Causal Heterogeneity Seriously: Implications for Case Choice and
           Case Study-Based Generalizations

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      Authors: Steffen Hertog
      Abstract: Sociological Methods & Research, Ahead of Print.
      In mixed methods approaches, statistical models are used to identify “nested” cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect sizes in individual cases—even if we choose “onlier” cases as is usually suggested. Contrary to established practice, we show that choosing “reinforcing” outlier cases—where outcomes are stronger than predicted in the statistical model—is appropriate for testing preexisting hypotheses on causal mechanisms, as this reduces the risk of false negatives. When investigating mechanisms inductively, researchers face a choice between “onlier” and reinforcing outlier cases that represents a trade-off between false negatives and false positives. We demonstrate that the inferential power of nested research designs can be much increased through paired comparisons of cases. More generally, this article provides a new conceptual framework for understanding the limits to and conditions for causal generalization from case studies.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-08T08:14:48Z
      DOI: 10.1177/0049124120986206
       
  • Contextual Text Coding: A Mixed-methods Approach for Large-scale Textual
           Data

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      Authors: Matty Lichtenstein, Zawadi Rucks-Ahidiana
      Abstract: Sociological Methods & Research, Ahead of Print.
      With the growing availability of large-scale text-based data sets, there is an increasing need for an accessible and systematic way to analyze qualitative texts. This article introduces and details the contextual text coding (CTC) method as a mixed-methods approach to large-scale qualitative data analysis. The method is particularly useful for complex text, textual data characterized by context-specific meanings and a lack of consistent terminology. CTC provides an alternative to current approaches to analyzing large textual data sets, specifically computational text analysis and hand coding, neither of which capture both the qualitative and quantitative analytical potential of large-scale textual data sets. Building on hand coding techniques and systematic sampling methods, CTC provides a clear six-step process to produce both quantitative and qualitative analyses of large-scale complex textual data sources. This article includes two examples, using projects focusing on journal and interview data, respectively, to illustrate the method’s versatility.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-08T08:13:48Z
      DOI: 10.1177/0049124120986191
       
  • The Living Codebook: Documenting the Process of Qualitative Data Analysis

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      Authors: Victoria Reyes, Elizabeth Bogumil, Levin Elias Welch
      Abstract: Sociological Methods & Research, Ahead of Print.
      Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we’ve collected. Although there are a few exceptions, less focus is on transparency regarding decision-making processes in the course of research. In this article, we argue that scholars should create a living codebook, which is a set of tools that documents the data analysis process. It has four parts: (1) a processual database that keeps track of initial codes and a final database for completed codes, (2) a “definitions and key terms” list for conversations about codes, (3) memo-writing, and (4) a difference list explaining the rationale behind unmatched codes. It allows researchers to interrogate taken-for-granted assumptions about what data are focused on, why, and how to analyze it. To that end, the living codebook moves beyond discussions around intercoder reliability to how analytic codes are created, refined, and debated.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-08T08:12:49Z
      DOI: 10.1177/0049124120986185
       
  • Transforming Family Resemblance Concepts into Fuzzy Sets

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      Authors: Francesco Veri
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article aims to clarify fundamental aspects of the process of assigning fuzzy scores to conditions based on family resemblance (FR) structures by considering prototype and set theories. Prototype theory and set theory consider FR structures from two different angles. Specifically, set theory links the conceptualization of FR to the idea of sufficient and INUS (Insufficient but Necessary part of a condition, which is itself Unnecessary but Sufficient for the result) sets. In contrast, concept membership in prototype theory is strictly linked to the notion of similarity (or resemblance) in relation to the prototype, which is the anchor of the ideational content of the concept. After an introductive section where I elucidate set-theoretic and prototypical aspects of concept formation, I individuate the axiomatic properties that identify the principles of transforming FR structures into fuzzy sets. Finally, I propose an algorithm based on the power mean that is able to operationalize FR structures considering both set-theoretic and prototype theory perspectives.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-05T09:34:18Z
      DOI: 10.1177/0049124120986196
       
  • Estimating the Uncertainty of a Small Area Estimator Based on a
           Microsimulation Approach

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      Authors: Angelo Moretti, Adam Whitworth
      Abstract: Sociological Methods & Research, Ahead of Print.
      Spatial microsimulation encompasses a range of alternative methodological approaches for the small area estimation (SAE) of target population parameters from sample survey data down to target small areas in contexts where such data are desired but not otherwise available. Although widely used, an enduring limitation of spatial microsimulation SAE approaches is their current inability to deliver reliable measures of uncertainty—and hence confidence intervals—around the small area estimates produced. In this article, we overcome this key limitation via the development of a measure of uncertainty that takes into account both variance and bias, that is, the mean squared error. This new approach is evaluated via a simulation study and demonstrated in a practical application using European Union Statistics on Income and Living Conditions data to explore income levels across Italian municipalities. Evaluations show that the approach proposed delivers accurate estimates of uncertainty and is robust to nonnormal distributions. The approach provides a significant development to widely used spatial microsimulation SAE techniques.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-04T09:18:32Z
      DOI: 10.1177/0049124120986199
       
  • Mobilizing the Masses: Measuring Resource Mobilization on Twitter

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      Authors: Amir Abdul Reda, Semuhi Sinanoglu, Mohamed Abdalla
      Abstract: Sociological Methods & Research, Ahead of Print.
      How can we measure the resource mobilization (RM) efforts of social movements on Twitter' In this article, we create the first ever measure of social movements’ RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM score that can be plotted in a time series format to track the RM efforts of social movements in real time. We use our tools with millions of tweets from the United States streamed between November 28, 2018, and February 11, 2019, to demonstrate how our measure can help us estimate the saliency and persistency of social movements’ RM efforts. We find that our measure captures RM by successfully cross checking the variation of this score against protest events in the United States during the same time frame. Finally, we illustrate the descriptive and qualitative utility of our tools for understanding social movements by running conventional topic modeling algorithms on the tweets that were used to compute the RM score and point at specific avenues for theory building and testing.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-04T09:16:52Z
      DOI: 10.1177/0049124120986197
       
  • The Effect of Question Positioning on Data Quality in Web Surveys

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      Authors: Cornelia Eva Neuert
      Abstract: Sociological Methods & Research, Ahead of Print.
      The quality of data in surveys is affected by response burden and questionnaire length. With an increasing number of questions, respondents can become bored, tired, and annoyed and may take shortcuts to reduce the effort needed to complete the survey. In this article, direct evidence is presented on how the position of items within a web questionnaire influences respondents’ focus of attention. In two experiments, part of an eye-tracking study and an online survey, respectively, a variety of indicators show that data quality is lower if the experimental question is positioned at the end rather than at the beginning of a questionnaire. Practical implications are discussed.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-03T09:08:31Z
      DOI: 10.1177/0049124120986207
       
  • A Method for Studying Differences in Segregation Across Time and Space

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      Authors: Benjamin Elbers
      Abstract: Sociological Methods & Research, Ahead of Print.
      An important topic in the study of segregation are comparisons across space and time. This article extends current approaches in segregation measurement by presenting a five-term decomposition procedure that can be used to understand more clearly why segregation has changed or differs between two comparison points. Two of the five terms account for differences in segregation that are due to the differing marginal distributions (e.g., the gender and occupational distributions), while one term accounts for differences in segregation due the different structure of segregation (what might be termed “pure” segregation). The decomposition thus presents a solution to the problem of margin dependency, frequently discussed in the segregation literature. Finally, two terms account for the appearance or disappearance of units when analyzing change over time. The method can be further extended to attribute structural changes to individual units, which makes it possible, for instance, to quantify the effect of each occupation on changing gender* segregation. The practical advantages of the decomposition are illustrated by two examples: a study of changing occupational gender segregation in the United States and a study of changing residential segregation in Brooklyn, New York.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-03T09:07:40Z
      DOI: 10.1177/0049124121986204
       
  • A Partial Simulation Study of Phantom Effects in Multilevel Analysis of
           School Effects: The Case of School Socioeconomic Composition

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      Authors: Hao Zhou, Xin Ma
      Abstract: Sociological Methods & Research, Ahead of Print.
      Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe the phenomenon in which the effects of student SES and school SES disappear once prior academic achievement is added to the model. In the present analysis, partial simulation (i.e., simulated data are used together with real-world data) was employed to examine the phantom effects of student SES and school SES on science achievement, using the national sample of the United States from the 2015 Programme for International Student Assessment. The results showed that the phantom effects of student SES and school SES are rather real. The stronger the correlation between prior science achievement and (present) science achievement, the greater the chance that the phantom effects occur.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-01T10:04:17Z
      DOI: 10.1177/0049124120986195
       
  • Combining Multiple Organizational-level Databases: An Empirical Evaluation
           of Different Matching Methods

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      Authors: Tim de Leeuw, Steffen Keijl
      Abstract: Sociological Methods & Research, Ahead of Print.
      Although multiple organizational-level databases are frequently combined into one data set, there is no overview of the matching methods (MMs) that are utilized because the vast majority of studies does not report how this was done. Furthermore, it is unclear what the differences are between the utilized methods, and it is unclear whether research findings might be influenced by the utilized method. This article describes four commonly used methods for matching databases and potential issues. An empirical comparison of those methods used to combine regularly used organizational-level databases reveals large differences in the number of observations obtained. Furthermore, empirical analyses of these different methods reveal that several of them produce both systematic and random errors. These errors can result in erroneous estimations of regression coefficients in terms of direction and/or size as well as an issue where truly significant relationships might be found to be insignificant. This shows that research findings can be influenced by the MM used, which would argue in favor of the establishment of a preferred method as well as more transparency on the utilized method in future studies. This article provides insight into the matching process and methods, suggests a preferred method, and should aid researchers, reviewers, and editors with both combining multiple databases and describing and assessing them.
      Citation: Sociological Methods & Research
      PubDate: 2021-02-01T03:09:38Z
      DOI: 10.1177/0049124120986184
       
  • A New Methodological Approach to Study Household Structure From Census and
           Survey Data

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      Authors: Simona Bignami-Van Assche, Virginie Boulet, Charles-Olivier Simard
      Abstract: Sociological Methods & Research, Ahead of Print.
      How household-level data from censuses and surveys are analyzed to study household structure is an issue that has received little attention. The present study proposes a new methodological approach to address this gap. Specifically, we introduce the idea of the household configuration as a mathematical representation of observations from the household roster that uses the tools of sequence analysis to study relationships between household members. This “household configuration approach” is statistically efficient, captures the heterogeneity of family forms in a population, and is computationally simple. An application to Canadian census data for Indigenous and non-Indigenous peoples shows that our approach can yield interesting insights into household structure, otherwise not readily obtained.
      Citation: Sociological Methods & Research
      PubDate: 2021-01-29T10:15:14Z
      DOI: 10.1177/0049124120986192
       
  • Is the Acknowledgment of Earned Entitlement Effect Robust Across
           Experimental Modes and Populations'

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      Authors: Abigail Barr, Luis Miller, Paloma Ubeda
      Abstract: Sociological Methods & Research, Ahead of Print.
      We present a set of studies the objective of which was to test the robustness of the acknowledgment of earned entitlement effect across different experimental modes and populations. We present three sets of results. The first is derived from a between-subject analysis of two independent, but comparable samples of nonstudent adults. One sample participated in a standard, behavioral laboratory experiment and the other participated in a survey experiment. The two methods returned similar treatment effects. The second set of results relates to a sample of students drawn from a behavioral laboratory’s pool of registered subjects. They participated in both the behavioral lab and survey experiments. We perform a between-subject comparison of the two treatment-elicitation methods but, this time, focusing on the same sample of subjects. Again, the treatment effects are very similar. Finally, we establish that within-subjects there is some consistency between decisions made under the two methods.
      Citation: Sociological Methods & Research
      PubDate: 2021-01-28T09:30:08Z
      DOI: 10.1177/0049124120986194
       
  • How to Interpret the Effect of Covariates on the Extreme Categories in
           Ordinal Data Models

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      Authors: Maria Iannario, Claudia Tarantola
      Abstract: Sociological Methods & Research, Ahead of Print.
      This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the response categories both in standard cumulative link models under the proportional odds assumption and in the recent extension of the Combination of Uncertainty and Preference of the respondents models, the mixture models introduced to account for uncertainty in rating systems. The article shows by means of marginal effect measures that the effects of the covariates are underestimated when the uncertainty component is neglected. Visualization tools for the effect of covariates are proposed, and measures of relative size and partial effect based on rates of change are evaluated by the use of real data sets.
      Citation: Sociological Methods & Research
      PubDate: 2021-01-28T09:29:11Z
      DOI: 10.1177/0049124120986179
       
  • Surveys in Communities Divided by Ethnicity and Conflict: Challenges,
           Possible Solutions, and Lessons Learned from a Survey in Jos, Nigeria

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      Authors: Peter Rudloff, Laura Thaut Vinson
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article details the challenges we faced in collecting sensitive information in an ethnically and religiously divided community that has experienced recent violence. The discussion is based on a summer 2016 survey experiment we conducted in Jos, Nigeria, to gather information regarding residents' perceptions of local communal violence. We discuss the challenges of such research and our approach to randomized sampling, constructing treatments that minimize the stress to respondents, debriefing to lower the possibility of spreading rumors of conflict, and utilizing computer tablets to increase access to the study for respondents with varying languages and levels of literacy. In particular, we discuss a geographic sampling method used for randomization, which we hope will prove useful to others facing similar randomization challenges.
      Citation: Sociological Methods & Research
      PubDate: 2021-01-28T09:28:29Z
      DOI: 10.1177/0049124120986175
       
 
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