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  Subjects -> STATISTICS (Total: 130 journals)
Showing 1 - 151 of 151 Journals sorted alphabetically
Advances in Complex Systems     Hybrid Journal   (Followers: 11)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 62)
Annals of Applied Statistics     Full-text available via subscription   (Followers: 39)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Argumentation et analyse du discours     Open Access   (Followers: 11)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 4)
Australian & New Zealand Journal of Statistics     Hybrid Journal   (Followers: 13)
Bernoulli     Full-text available via subscription   (Followers: 9)
Biometrical Journal     Hybrid Journal   (Followers: 11)
Biometrics     Hybrid Journal   (Followers: 52)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Building Simulation     Hybrid Journal   (Followers: 2)
Bulletin of Statistics     Full-text available via subscription   (Followers: 4)
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: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 37)
Current Research in Biostatistics     Open Access   (Followers: 8)
Decisions in Economics and Finance     Hybrid Journal   (Followers: 11)
Demographic Research     Open Access   (Followers: 15)
Electronic Journal of Statistics     Open Access   (Followers: 8)
Engineering With Computers     Hybrid Journal   (Followers: 5)
Environmental and Ecological Statistics     Hybrid Journal   (Followers: 7)
ESAIM: Probability and Statistics     Full-text available via subscription   (Followers: 5)
Extremes     Hybrid Journal   (Followers: 2)
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 9)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 13)
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: 3)
International Statistical Review     Hybrid Journal   (Followers: 13)
International Trade by Commodity Statistics - Statistiques du commerce international par produit     Full-text available via subscription  
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 4)
Journal of Applied Statistics     Hybrid Journal   (Followers: 21)
Journal of Biopharmaceutical Statistics     Hybrid Journal   (Followers: 21)
Journal of Business & Economic Statistics     Full-text available via subscription   (Followers: 39, SJR: 3.664, CiteScore: 2)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Computational & Graphical Statistics     Full-text available via subscription   (Followers: 20)
Journal of Econometrics     Hybrid Journal   (Followers: 84)
Journal of Educational and Behavioral Statistics     Hybrid Journal   (Followers: 6)
Journal of Forecasting     Hybrid Journal   (Followers: 17)
Journal of Global Optimization     Hybrid Journal   (Followers: 7)
Journal of Interactive Marketing     Hybrid Journal   (Followers: 10)
Journal of Mathematics and Statistics     Open Access   (Followers: 8)
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: 5)
Journal of Statistical Physics     Hybrid Journal   (Followers: 13)
Journal of Statistical Planning and Inference     Hybrid Journal   (Followers: 8)
Journal of Statistical Software     Open Access   (Followers: 21, 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   (Followers: 1)
Journal of the Royal Statistical Society Series C (Applied Statistics)     Hybrid Journal   (Followers: 33)
Journal of the Royal Statistical Society, Series A (Statistics in Society)     Hybrid Journal   (Followers: 27)
Journal of the Royal Statistical Society, Series B (Statistical Methodology)     Hybrid Journal   (Followers: 43)
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: 30)
Law, Probability and Risk     Hybrid Journal   (Followers: 8)
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)
Modelling of Mechanical Systems     Full-text available via subscription   (Followers: 1)
Monte Carlo Methods and Applications     Hybrid Journal   (Followers: 6)
Monthly Statistics of International Trade - Statistiques mensuelles du commerce international     Full-text available via subscription   (Followers: 2)
Multivariate Behavioral Research     Hybrid Journal   (Followers: 5)
Optimization Letters     Hybrid Journal   (Followers: 2)
Optimization Methods and Software     Hybrid Journal   (Followers: 8)
Oxford Bulletin of Economics and Statistics     Hybrid Journal   (Followers: 34)
Pharmaceutical Statistics     Hybrid Journal   (Followers: 17)
Probability Surveys     Open Access   (Followers: 4)
Queueing Systems     Hybrid Journal   (Followers: 7)
Research Synthesis Methods     Hybrid Journal   (Followers: 8)
Review of Economics and Statistics     Hybrid Journal   (Followers: 128)
Review of Socionetwork Strategies     Hybrid Journal  
Risk Management     Hybrid Journal   (Followers: 15)
Sankhya A     Hybrid Journal   (Followers: 2)
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: 38)
SourceOCDE Comptes nationaux et Statistiques retrospectives     Full-text available via subscription  
SourceOCDE Statistiques : Sources et methodes     Full-text available via subscription  
SourceOECD Bank Profitability Statistics - SourceOCDE Rentabilite des banques     Full-text available via subscription   (Followers: 1)
SourceOECD Insurance Statistics - SourceOCDE Statistiques d'assurance     Full-text available via subscription   (Followers: 2)
SourceOECD Main Economic Indicators - SourceOCDE Principaux indicateurs economiques     Full-text available via subscription   (Followers: 1)
SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques     Full-text available via subscription  
SourceOECD Monthly Statistics of International Trade     Full-text available via subscription   (Followers: 1)
SourceOECD National Accounts & Historical Statistics     Full-text available via subscription  
SourceOECD OECD Economic Outlook Database - SourceOCDE Statistiques des Perspectives economiques de l'OCDE     Full-text available via subscription   (Followers: 2)
SourceOECD Science and Technology Statistics - SourceOCDE Base de donnees des sciences et de la technologie     Full-text available via subscription  
SourceOECD Statistics Sources & Methods     Full-text available via subscription   (Followers: 1)
SourceOECD Taxing Wages Statistics - SourceOCDE Statistiques des impots sur les salaires     Full-text available via subscription  
Stata Journal     Full-text available via subscription   (Followers: 9)
Statistica Neerlandica     Hybrid Journal   (Followers: 1)
Statistical Applications in Genetics and Molecular Biology     Hybrid Journal   (Followers: 5)
Statistical Communications in Infectious Diseases     Hybrid Journal  
Statistical Inference for Stochastic Processes     Hybrid Journal   (Followers: 3)
Statistical Methodology     Hybrid Journal   (Followers: 7)
Statistical Methods and Applications     Hybrid Journal   (Followers: 6)
Statistical Methods in Medical Research     Hybrid Journal   (Followers: 27)
Statistical Modelling     Hybrid Journal   (Followers: 19)
Statistical Papers     Hybrid Journal   (Followers: 4)
Statistical Science     Full-text available via subscription   (Followers: 13)
Statistics & Probability Letters     Hybrid Journal   (Followers: 13)
Statistics & Risk Modeling     Hybrid Journal   (Followers: 3)
Statistics and Computing     Hybrid Journal   (Followers: 13)
Statistics and Economics     Open Access   (Followers: 1)
Statistics in Medicine     Hybrid Journal   (Followers: 196)
Statistics, Politics and Policy     Hybrid Journal   (Followers: 6)
Statistics: A Journal of Theoretical and Applied Statistics     Hybrid Journal   (Followers: 15)
Stochastic Models     Hybrid Journal   (Followers: 3)
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: 7)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TEST     Hybrid Journal   (Followers: 3)
The American Statistician     Full-text available via subscription   (Followers: 23)
The Annals of Applied Probability     Full-text available via subscription   (Followers: 8)
The Annals of Probability     Full-text available via subscription   (Followers: 10)
The Annals of Statistics     Full-text available via subscription   (Followers: 34)
The Canadian Journal of Statistics / La Revue Canadienne de Statistique     Hybrid Journal   (Followers: 11)
Wiley Interdisciplinary Reviews - Computational Statistics     Hybrid Journal   (Followers: 1)

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Similar Journals
Journal Cover
Sociological Methods & Research
Journal Prestige (SJR): 2.35
Citation Impact (citeScore): 3
Number of Followers: 38  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0049-1241 - ISSN (Online) 1552-8294
Published by Sage Publications Homepage  [1141 journals]
  • The Grievance Studies Affair; One Funeral at a Time: A Reply to Lindsay,
           Pluckrose, and Boghossian
    • Authors: Geoff G. Cole
      Abstract: Sociological Methods & Research, Ahead of Print.
      In 2018, Lindsay, Pluckrose, and Boghossian published four “hoax” articles within a number of disciplines that rely on critical theory (e.g., gender studies, feminism). When revealing the project, the authors argued that they wanted to expose these fields as being primarily motivated by ideology and social justice rather than knowledge generation. Their method tested the hypothesis that editors and reviewers will support papers that advocate “ludicrous” ideas including “fat bodybuilding.” In the pages of this journal, I presented a critique of their procedure, and the authors have provided a commentary on my article. After discussing the issue of whether their project was a hoax or not, I will argue that the crux of the matter is whether the papers were ludicrous/absurd. I will show how the authors made a fundamental error in their method; they failed to assess whether their ideas were indeed ludicrous/absurd.
      Citation: Sociological Methods & Research
      PubDate: 2021-04-30T06:27:41Z
      DOI: 10.1177/00491241211009949
  • Marginal and Conditional Confounding Using Logits
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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
    • 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'
    • 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
    • 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
    • Authors: Peter Rudloff, Laura Thaut Vinson
      Abstract: Sociological Methods & Research, Ahead of Print.
      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
  • Practical Methods for Imputing Follower Count Dynamics
    • Authors: C. Ben Gibson, Jeannette Sutton, Sarah K. Vos, Carter T. Butts
      Abstract: Sociological Methods & Research, Ahead of Print.
      Microblogging sites have become important data sources for studying network dynamics and information transmission. Both areas of study, however, require accurate counts of indegree, or follower counts; unfortunately, collection of complete time series on follower counts can be limited by application programming interface constraints, system failures, or temporal constraints. In addition, there is almost always a time difference between the point at which follower counts are queried and the time a user posts a tweet. Here, we consider the use of three classes of simple, easily implemented methods for follower imputation: polynomial functions, splines, and generalized linear models. We evaluate the performance of each method via a case study of accounts from 236 health organizations during the 2014 Ebola outbreak. For accurate interpolation and extrapolation, we find that negative binomial regression, modeled separately for each account, using time as an interval variable, accurately recovers missing values while retaining narrow prediction intervals.
      Citation: Sociological Methods & Research
      PubDate: 2020-07-29T09:47:09Z
      DOI: 10.1177/0049124120926210
  • How to Borrow Information From Unlinked Data' A Relative Density
           Approach for Predicting Unobserved Distributions
    • Authors: Siwei Cheng
      Abstract: Sociological Methods & Research, Ahead of Print.
      One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information across unlinked data can be much more challenging due to the absence of unit-to-unit linkages. This article proposes a new methodological approach for borrowing information across unlinked surveys to predict unobserved distributions. The gist of the proposed approach lies in the idea of using the relative density between the observed and unobserved distributions in the reference data to characterize the difference between the two distributions and borrow that information to the base data. Relying on the assumption that the relative density between the observed and unobserved distributions is similar between data sets, the proposed relative density approach has the key advantage of allowing the researcher to borrow information about the shape of the distribution, rather than a few summary statistics. The approach also comes with a method for incorporating and quantifying the uncertainty in its output. We illustrate the formulation of this approach, demonstrate with simulation examples, and finally apply it to address the problem of employment selection in wage inequality research.
      Citation: Sociological Methods & Research
      PubDate: 2020-07-10T09:37:32Z
      DOI: 10.1177/0049124120926214
  • Making Things Possible
    • Authors: Gabriel Abend
      Abstract: Sociological Methods & Research, Ahead of Print.
      I argue that what-makes-it-possible questions are a distinct and important kind of sociological research question. What is social phenomenon P made possible or enabled by' Results won’t be about P’s causes and causal relationships, but about its enablers and enabling relationships. I examine the character of what-makes-it-possible questions and claims, how they can be empirically investigated, and what they’re good for. If I’m right, they provide a unique perspective on social phenomena, they show how the social world doesn’t come ready-made, and they open up new avenues for research.
      Citation: Sociological Methods & Research
      PubDate: 2020-07-10T09:34:32Z
      DOI: 10.1177/0049124120926204
  • Critical Event Analysis in Case Study Research
    • Authors: Laura García-Montoya, James Mahoney
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article develops a framework for the causal analysis of critical events in case study research. A critical event is defined as a contingent event that is causally important for an outcome in a specific case. Using set-theoretic analysis, this article offers definitions and measurement tools for the study of contingency and causal importance in case study research. One set of tools consists of guidelines for using theoretical expectations to arrive at conclusions about the level of contingency of events. Another set of tools are guidelines for using counterfactual cases to determine the extent to which a given event is necessary and sufficient for a particular outcome in an individual case. Examples from comparative and international studies are used to illustrate the framework.
      Citation: Sociological Methods & Research
      PubDate: 2020-07-08T10:39:16Z
      DOI: 10.1177/0049124120926201
  • Μeasuring and Visualizing Coders’ Reliability: New Approaches and
           Guidelines From Experimental Data
    • Authors: Iasonas Lamprianou
      Abstract: Sociological Methods & Research, Ahead of Print.
      This study investigates inter- and intracoder reliability, proposing a new approach based on social network analysis (SNA) and exponential random graph models (ERGM). During a recent exit poll, the responses of voters to two open-ended questions were recorded. A coding experiment was conducted where a group of coders coded a sample of text segments. Analyzing the data, we show that the proposed SNA/ERGM method extends significantly our analytical leverage, beyond what popular tools such as Krippendorff’s α and Fleiss’s κ have to offer. The reliability of coding for individual coders differed significantly for the two questions although they were very similar and the same codebook was used. We conclude that the main advantages of the proposed SNA/ERGM method are the intuitive visualizations and the nuanced measurements. Detailed guidelines are provided for practitioners who would like to use the proposed method in operational settings.
      Citation: Sociological Methods & Research
      PubDate: 2020-06-24T09:17:11Z
      DOI: 10.1177/0049124120926198
  • Interpersonal Perceptions and Interviewer Effects in Face-to-Face Surveys
    • Authors: Simon Kühne
      Abstract: Sociological Methods & Research, Ahead of Print.
      Survey interviewers can negatively affect survey data by introducing variance and bias into estimates. When investigating these interviewer effects, research typically focuses on interviewer sociodemographics with only a few studies examining the effects of characteristics that are not directly visible such as interviewer attitudes, opinions, and personality. For the study at hand, self-reports of 1,212 respondents and 116 interviewers, as well as their interpersonal perceptions of each other, were collected in a large-scale, face-to-face survey of households in Germany. Respondents and interviewers were presented with the same questions regarding their opinions and mutual perceptions toward social and political issues in Germany. Analyses show that interviewer effects can be largely explained by how an interviewer is seen by respondents. This indicates that some respondents adjust their answers toward anticipated interviewer opinions. Survey practitioners ought to acknowledge this in their survey design and training of interviewers.
      Citation: Sociological Methods & Research
      PubDate: 2020-06-15T08:58:44Z
      DOI: 10.1177/0049124120926215
  • Fixed Effects Individual Slopes: Accounting and Testing for Heterogeneous
           Effects in Panel Data or Other Multilevel Models
    • Authors: Tobias Rüttenauer, Volker Ludwig
      Abstract: Sociological Methods & Research, Ahead of Print.
      Fixed effects (FE) panel models have been used extensively in the past, as those models control for all stable heterogeneity between units. Still, the conventional FE estimator relies on the assumption of parallel trends between treated and untreated groups. It returns biased results in the presence of heterogeneous slopes or growth curves that are related to the parameter of interest (e.g., selection into treatment is based on individual growth of the outcome). In this study, we derive the bias in conventional FE models and show that fixed effects individual slope (FEIS) models can overcome this problem. This is a more general version of the conventional FE model, which accounts for heterogeneous slopes or trends, thereby providing a powerful tool for panel data and other multilevel data in general. We propose two versions of the Hausman test that can be used to identify misspecification in FE models. The performance of the FEIS estimator and the specification tests is evaluated in a series of Monte Carlo experiments. Using the examples of the marital wage premium and returns to preschool education (Head Start), we demonstrate how taking heterogeneous effects into account can seriously change the conclusions drawn from conventional FE models. Thus, we propose to test for bias in FE models in practical applications and to apply FEIS if indicated by the specification tests.
      Citation: Sociological Methods & Research
      PubDate: 2020-06-10T06:54:53Z
      DOI: 10.1177/0049124120926211
  • The Structure of Academic Achievement: Searching for Proximal Mechanisms
           Using Causal Discovery Algorithms
    • Authors: Rafael Quintana
      Abstract: Sociological Methods & Research, Ahead of Print.
      Causal search algorithms have been effectively applied in different fields including biology, genetics, climate science, medicine, and neuroscience. However, there have been scant applications of these methods in social and behavioral sciences. This article provides an illustrative example of how causal search algorithms can shed light on important social and behavioral problems by using these algorithms to find the proximal mechanisms of academic achievement. Using a nationally representative data set with a wide range of relevant contextual and psychological factors, I implement four causal search procedures that varied important dimensions in the algorithms. Consistent with previous research, the algorithms identified prior achievement, executive functions (in particular, working memory, cognitive flexibility, and attentional focusing), and motivation as direct causes of academic achievement. I discuss the advantages and limitations of graphical models in general and causal search algorithms in particular for understanding social and behavioral problems.
      Citation: Sociological Methods & Research
      PubDate: 2020-06-09T09:34:36Z
      DOI: 10.1177/0049124120926208
  • Letting a Picture Speak a Thousand Words: Arts-based Research in a Study
           of the Careers of Female Academics
    • Authors: Fleur Sharafizad, Kerry Brown, Uma Jogulu, Maryam Omari
      Abstract: Sociological Methods & Research, Ahead of Print.
      This article presents an adaptation of an arts-based research method usually reserved for child-focused research to examine organizational processes. We developed Draw, Write, Reflect (DWR), advancing a known method, Draw and Write, for investigating phenomena relating to child participants, to explore a new context: adults engaging in academic careers. This article reports on the rationale behind the novel use of this research method, outlines a DWR procedure for future research, and contains reflections of both the researchers and the respondents regarding their experiences participating in DWR. Offering participants a combination of visual and oral methods allowed the researchers to obtain data in a more individualized approach steered by participants’ preferences. The multidimensional insights obtained through DWR would not have been attainable through each method on its own. Furthermore, we argue arts-based research can serve as a vehicle for disseminating academic work beyond conventional academe to a growing, nonacademic audience.
      Citation: Sociological Methods & Research
      PubDate: 2020-05-28T10:39:01Z
      DOI: 10.1177/0049124120926206
  • Mitigating Selection Bias: A Bayesian Approach to Two-stage Causal
           Modeling With Instrumental Variables for Nonnormal Missing Data
    • Authors: Dingjing Shi, Xin Tong
      Abstract: Sociological Methods & Research, Ahead of Print.
      This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student’s t distributions are used to account for nonnormal data. Ignorable missing data are handled by multiple imputation techniques, while nonignorable missing data are handled by an added-on selection model structure. In addition to categorical treatment data, this study extends the work to continuous treatment variables. Monte Carlo simulation studies are conducted showing that the proposed Bayesian approach can well address common issues in existing methods. We provide a real data example on the early childhood relative age effect study to illustrate the application of the proposed method. The proposed method can be easily implemented using the R software package "ALMOND" (Analysis of Local Average Treatment Effect for missing or/and Nonnormal Data).
      Citation: Sociological Methods & Research
      PubDate: 2020-05-20T09:23:32Z
      DOI: 10.1177/0049124120914920
  • Response Quality in Nonprobability and Probability-based Online Panels
    • Authors: Carina Cornesse, Annelies G. Blom
      Abstract: Sociological Methods & Research, Ahead of Print.
      Recent years have seen a growing number of studies investigating the accuracy of nonprobability online panels; however, response quality in nonprobability online panels has not yet received much attention. To fill this gap, we investigate response quality in a comprehensive study of seven nonprobability online panels and three probability-based online panels with identical fieldwork periods and questionnaires in Germany. Three response quality indicators typically associated with survey satisficing are assessed: straight-lining in grid questions, item nonresponse, and midpoint selection in visual design experiments. Our results show that there is significantly more straight-lining in the nonprobability online panels than in the probability-based online panels. However, contrary to our expectations, there is no generalizable difference between nonprobability online panels and probability-based online panels with respect to item nonresponse. Finally, neither respondents in nonprobability online panels nor respondents in probability-based online panels are significantly affected by the visual design of the midpoint of the answer scale.
      Citation: Sociological Methods & Research
      PubDate: 2020-05-06T10:11:36Z
      DOI: 10.1177/0049124120914940
  • Interactions in Fixed Effects Regression Models
    • Authors: Marco Giesselmann, Alexander W. Schmidt-Catran
      Abstract: Sociological Methods & Research, Ahead of Print.
      An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, algebraic transformations reveal that this strategy does not yield a within-unit estimator. Instead, the standard FE interaction estimator reflects unit-level differences of the interacted variables. This property allows interactions of a time-constant variable and a time-varying variable in FE to be estimated but may yield unwanted results if both variables vary within units. In such cases, Monte Carlo experiments confirm that the standard FE estimator of x ⋅ z is biased if x is correlated with an unobserved unit-specific moderator of z (or vice versa). A within estimator of an interaction can be obtained by first demeaning each variable and then demeaning their product. This “double-demeaned” estimator is not subject to bias caused by unobserved effect heterogeneity. It is, however, less efficient than standard FE and only works with T> 2.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-28T09:47:08Z
      DOI: 10.1177/0049124120914934
  • Applying and Assessing Large-N QCA: Causality and Robustness From a
           Critical Realist Perspective
    • Authors: Roel Rutten
      Abstract: Sociological Methods & Research, Ahead of Print.
      Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers’ case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method, QCA is designed to be sensitive to such tests, meaning that also large-N QCA robustness tests must be evaluated against substantive knowledge. This article connects QCA’s substantive-interpretation approach of causality to critical realism. From that perspective, it identifies relevant robustness tests and applies them to a real-data large-N QCA study. Robustness test findings are visualized in a robustness table, and this article develops criteria to substantively interpret them. The robustness table is introduced as a tool to substantiate the validity of causal claims in large-N QCA studies.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-27T06:43:37Z
      DOI: 10.1177/0049124120914955
  • Intensive Family Observations: A Methodological Guide
    • Authors: Annette Lareau, Aliya Hamid Rao
      Abstract: Sociological Methods & Research, Ahead of Print.
      There is a dearth of methodological guidance on how to conduct participant observation in private spaces such as family homes. Yet, participant observations can provide deep and valuable data about family processes. This article draws on two ethnographic studies of family life in which researchers conduct in-depth interviews, recruit families, and ultimately enter the family as a quasi-stranger for daily observations lasting a fixed period (e.g., three weeks). We term this approach “intensive family observations.” Here, we provide concrete methodological advice for this method, beginning with guidelines for recruitment and gaining consent. We also discuss logistics of conducting family observation (e.g., scheduling, spatial positionality in the home, role in the field, among other issues). We elaborate on the key challenges, specifically issues of intrusion, power, and positionality. Last, we reflect on how this method provides opportunities for accurately capturing deeply intimate moments as well as unexpected insights.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-24T09:45:50Z
      DOI: 10.1177/0049124120914949
  • Q-SpAM: How to Efficiently Measure Similarity in Online Research
    • Authors: Alex Koch, Felix Speckmann, Christian Unkelbach
      Abstract: Sociological Methods & Research, Ahead of Print.
      Measuring the similarity of stimuli is of great interest to a variety of social scientists. Spatial arrangement by dragging and dropping “more similar” targets closer together on the computer screen is a precise and efficient method to measure stimulus similarity. We present Qualtrics-spatial arrangement method (Q-SpAM), a feature-rich and user-friendly online version of spatial arrangement. Combined with crowdsourcing platforms, Q-SpAM provides fast and affordable access to similarity data even for large stimulus sets. Participants may spatially arrange up to 100 words or images, randomly selected targets, self-selected targets, self-generated targets, and targets self-marked in different colors. These and other Q-SpAM features can be combined. We exemplify how to collect, process, and visualize similarity data with Q-SpAM and provide R and Excel scripts to do so. We then illustrate Q-SpAM’s versatility for social science, concluding that Q-SpAM is a reliable and valid method to measure the similarity of lots of stimuli with little effort.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-24T09:43:10Z
      DOI: 10.1177/0049124120914937
  • Joint Modeling of Multivariate Survival Data With an Application to
    • Authors: Grace Li, Mary Lesperance, Zheng Wu
      Abstract: Sociological Methods & Research, Ahead of Print.
      The Cox proportional hazards model has been pervasively used in many social science areas to examine the effects of covariates on timing to an event. The standard Cox model is intended to study univariate survival data where there is a singular event of interest, which can only be experienced once. However, we may additionally wish to explore a number of other complexities that are prevalent in survival data. For example, an individual may experience events of the same type more than once or may experience multiple types of events. This study introduces innovations in recurrent (repeatable) event analysis, jointly modeling several endogenous survival processes. As an example and an application, we simultaneously model two types of recurrent events in the presence of a dependent terminal event. This model not only correctly handles different types of recurrent events but also explicitly estimates the direction and magnitude of relationships between recurrences and survival. This article concludes with an example of the model to examine how the timing of retirement is associated with the risks of multiple spells of employment and childbearing. The theoretical discussions and empirical analyses suggest that the multivariate joint models have much to offer to a wide variety of substantive research areas.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-24T09:40:43Z
      DOI: 10.1177/0049124120914928
  • Early and Late Participation during the Field Period: Response Timing in a
           Mixed-Mode Probability-Based Panel Survey
    • Authors: Tobias Gummer, Bella Struminskaya
      Abstract: Sociological Methods & Research, Ahead of Print.
      Reluctance of respondents to participate in surveys has long drawn the attention of survey researchers. Yet, little is known about what drives a respondent’s decision to answer the survey invitation early or late during the field period. Moreover, we still lack evidence on response timing in longitudinal surveys. That is, the questions on whether response timing is a rather stable respondent characteristic and what—if anything—affects change in response timing across different interviews remain open. We relied on data from a mixed-mode general population panel survey collected between 2014 and 2016 to study the stability of response timing across 18 panel waves and factors that influence the decision to participate early or late in the field period. Our results suggest that the factors which had effects on response timing are different in the mail and web modes. Moreover, we found that experience with prior panel waves affected the respondent’s decision to participate early or late. Overall, the present study advocates understanding response timing as a metric variable and, consequently, the need to reflect this in modeling strategies.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-22T10:04:32Z
      DOI: 10.1177/0049124120914921
  • A Logistic Regression Extension for the Randomized Response Simple and
           Crossed Models: Theoretical Results and Empirical Evidence
    • Authors: Shu-Hui Hsieh, Pier Francesco Perri
      Abstract: Sociological Methods & Research, Ahead of Print.
      We propose some theoretical and empirical advances by supplying the methodology for analyzing the factors that influence two sensitive variables when data are collected by randomized response (RR) survey modes. First, we provide the framework for obtaining the maximum likelihood estimates of logistic regression coefficients under the RR simple and crossed models, then we carry out a simulation study to assess the performance of the estimation procedure. Finally, logistic regression analysis is illustrated by considering real data about cannabis use and legalization and about abortion and illegal immigration. The empirical results bring out certain considerations about the effect of the RR and direct questioning survey modes on the estimates. The inference about the sign and the significance of the regression coefficients can contribute to the debate on whether the RR approach is an effective survey method to reduce misreporting and improve the validity of analyses.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-20T10:18:13Z
      DOI: 10.1177/0049124120914950
  • Methodological Issues When Interpreting Changes in Social Phenomena Over
           Time: Perceptions of Relative Difference, Absolute Difference, and Time
    • Authors: Katja Prevodnik, Vasja Vehovar
      Abstract: Sociological Methods & Research, Ahead of Print.
      When comparing social science phenomena through a time perspective, absolute and relative difference (RD) are the two typical presentation formats used to communicate interpretations to the audience, while time distance (TD) is the least frequently used of such formats. This article argues that the chosen presentation format is extremely important because the various formats suggest different substantive interpretations. To elaborate upon this issue, researchers from the National Statistical Office, National Health Institute, and general academia were invited to participate in an experiment with alternative presentation formats that describe changes in certain social science phenomena over time. The results revealed a prevailing tendency of respondents to rely on interpretations related to absolute differences, which was additionally reinforced with graphical presentation formats. Therefore, whenever RD or TD is more proper for substantive interpretations, the corresponding presentation format must be designed with special attention.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-20T10:08:13Z
      DOI: 10.1177/0049124120914948
  • Clustered Iconography: A Resurrected Method for Representing
           Multidimensional Data
    • Authors: Olav Muurlink, Anthony M. Gould, Jean-Etienne Joullié
      Abstract: Sociological Methods & Research, Ahead of Print.
      Development of graphical methods for representing data has not kept up with progress in statistical techniques. This article presents a brief history of graphical representations of research findings and makes the case for a revival of methods developed in the early and mid-twentieth century, notably ISOTYPE and Chernoff’s faces. It resurrects and improves a procedure, clustered iconography, which enables the presentation of multidimensional data through which readers engage more effectively with the presentation’s central message by way of an easier understanding of relationships between variables. The proposed technique is especially well adapted to the needs and protocols of open-source research.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-10T10:30:49Z
      DOI: 10.1177/0049124120914943
  • Model Adequacy Checking/Goodness-of-fit Testing for Behavior in Joint
           Dynamic Network/Behavior Models, with an Extension to Two-mode Networks
    • Authors: Cheng Wang, Carter T. Butts, John Hipp, Cynthia M. Lakon
      Abstract: Sociological Methods & Research, Ahead of Print.
      The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to reproduce network structure over time, to date there are few indices for assessing the ability of the model to reproduce individuals’ behavior patterns. Drawing on the widely used strategy of assessing model adequacy by comparing index values summarizing features of the observed data to the distribution of those index values on simulated data from the fitted model, we propose four goals that a researcher could reasonably expect of a joint structure/behavior model regarding how well it captures behavior and describe indices for assessing each of these. These reasonably simple and easily implemented indices can be used for assessing model adequacy with any dynamic network models jointly working with networks and behavior, including the stochastic actor-based models implemented within software packages such as RSien version 1.2-24. We demonstrate the use of our indices with an empirical example to show how they can be employed in practical settings, with an additional extension to modeling affiliation dynamics in two-mode networks. Key scripts are provided in the Supplemental Document (which can be found at http://smr.sagepub.com/supplemental/).
      Citation: Sociological Methods & Research
      PubDate: 2020-04-10T10:15:08Z
      DOI: 10.1177/0049124120914933
  • Cheater Detection Using the Unrelated Question Model
    • Authors: Fabiola Reiber, Harrison Pope, Rolf Ulrich
      Abstract: Sociological Methods & Research, Ahead of Print.
      Randomized response techniques (RRTs) are useful survey tools for estimating the prevalence of sensitive issues, such as the prevalence of doping in elite sports. One type of RRT, the unrelated question model (UQM), has become widely used because of its psychological acceptability for study participants and its favorable statistical properties. One drawback of this model, however, is that it does not allow for detecting cheaters—individuals who disobey the survey instructions and instead give self-protecting responses. In this article, we present refined versions of the UQM designed to detect the prevalence of cheating responses. We provide explicit formulas to calculate the parameters of these refined UQM versions and show how the empirical adequacy of these versions can be tested. The Appendices contain R-code for all necessary calculations.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-10T10:08:48Z
      DOI: 10.1177/0049124120914919
  • Why the “Hoax” Paper of Baldwin (2018) Should Be Reinstated
    • Authors: Geoff G. Cole
      Abstract: Sociological Methods & Research, Ahead of Print.
      In 2018, a peer-reviewed article was published under the name of Richard Baldwin in which the author presented a critique of fat exclusion and advocated “fat bodybuilding” as a sport. Some months later, it became apparent that the article was intended as a hoax written to raise awareness to, or “expose”, a certain ideology promoted by some academics. As a result, the editors retracted the article. Using the principles of methodological behaviorism, and other hoax or hoax-like articles, I will argue that the thoughts and opinions held by any author are not important to the argument they present. I will also argue that this form of reflexive ethnography is too problematic to serve as a method of enquiry. I will therefore conclude that the Baldwin article should be reinstated.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-09T09:49:04Z
      DOI: 10.1177/0049124120914951
  • Improved Estimation of Poisson Rate Distributions Through a Multimode
           Survey Design
    • Authors: Marcin Hitczenko
      Abstract: Sociological Methods & Research, Ahead of Print.
      Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more accurate, but their greater cost and respondent burden generally yield less data. The choice of survey mode, therefore, involves a potential trade-off between bias and variance of estimators. We use a case study comparing inferences about payment instrument use based on different survey designs to illustrate this dilemma. We then use a simulation study to show how and under what conditions a hybrid survey design can improve efficiency of estimation, in terms of mean-squared error. Overall, our work suggests that such a hybrid design can have considerable benefits, as long as there is nontrivial overlap in the diary and recall samples.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-09T09:47:25Z
      DOI: 10.1177/0049124119882465
  • Effects of Partner Presence During the Interview on Survey Responses: The
           Example of Questions Concerning the Division of Household Labor
    • Authors: Jette Schröder, Claudia Schmiedeberg
      Abstract: Sociological Methods & Research, Ahead of Print.
      Despite the fact that third parties are present during a substantial amount of face-to-face interviews, bystander influence on respondents’ response behavior is not yet fully understood. We use nine waves of the German Family Panel pairfam and apply fixed effects panel regression models to analyze effects of third-party presence on items regarding the sharing of household tasks between partners. We find that both male and female respondents report doing a smaller share of household tasks when their partner is present during the interview as compared to when their partner is not present. Similarly, if the respondent’s partner is present, both partners’ reports correspond more, so that they are less prone to resulting in unrealistically high sums. These results indicate that for items concerning household labor, partner presence does not compromise data quality but may in fact improve it.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-07T10:22:51Z
      DOI: 10.1177/0049124120914938
  • Coverage Error in Data Collection Combining Mobile Surveys With Passive
           Measurement Using Apps: Data From a German National Survey
    • Authors: Florian Keusch, Sebastian Bähr, Georg-Christoph Haas, Frauke Kreuter, Mark Trappmann
      Abstract: Sociological Methods & Research, Ahead of Print.
      Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data can be collected passively. These limitations cause concern about coverage error in studies targeting the general population. Based on data from the Panel Study Labour Market and Social Security (PASS), an annual probability-based mixed-mode survey on the labor market and poverty in Germany, we find that smartphone ownership and ownership of smartphones with specific OSs are correlated with a number of sociodemographic and substantive variables. The use of weighting techniques based on sociodemographic information available for both owners and nonowners reduces these differences but does not eliminate them.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-07T10:20:51Z
      DOI: 10.1177/0049124120914924
  • The probability of a robust inference for internal validity
    • Authors: Tenglong Li, Ken Frank
      Abstract: Sociological Methods & Research, Ahead of Print.
      The internal validity of observational study is often subject to debate. In this study, we define the counterfactuals as the unobserved sample and intend to quantify its relationship with the null hypothesis statistical testing (NHST). We propose the probability of a robust inference for internal validity, that is, the PIV, as a robustness index of causal inference. Formally, the PIV is the probability of rejecting the null hypothesis again based on both the observed sample and the counterfactuals, provided the same null hypothesis has already been rejected based on the observed sample. Under either frequentist or Bayesian framework, one can bound the PIV of an inference based on his bounded belief about the counterfactuals, which is often needed when the unconfoundedness assumption is dubious. The PIV is equivalent to statistical power when the NHST is thought to be based on both the observed sample and the counterfactuals. We summarize the process of evaluating internal validity with the PIV into a six-step procedure and illustrate it with an empirical example.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-07T10:18:51Z
      DOI: 10.1177/0049124120914922
  • A Two-stage Multilevel Randomized Response Technique With Proportional
           Odds Models and Missing Covariates
    • Authors: Shu-Hui Hsieh, Shen-Ming Lee, Chin-Shang Li
      Abstract: Sociological Methods & Research, Ahead of Print.
      Surveys of income are complicated by the sensitive nature of the topic. The problem researchers face is how to encourage participants to respond and to provide truthful responses in surveys. To correct biases induced by nonresponse or underreporting, we propose a two-stage multilevel randomized response (MRR) technique to investigate the true level of income and to protect personal privacy. For a wide range of applications, we present a proportional odds model for two-stage MRR data and apply inverse probability weighting and multiple imputation methods to deal with covariates on some subjects that are missing at random. A simulation study is conducted to investigate the effects of missing covariates and to evaluate the performance of the proposed methods. The practicality of the proposed methods is illustrated with the regular monthly income data collected in the Taiwan Social Change Survey. Furthermore, we provide an estimate of personal regular monthly mean income.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-03T10:35:20Z
      DOI: 10.1177/0049124120914954
  • Using Location Data From Mobile Phones to Study Participation in Mass
    • Authors: Assaf Rotman, Michael Shalev
      Abstract: Sociological Methods & Research, Ahead of Print.
      Automatically collected behavioral data on the location of users of mobile phones offer an unprecedented opportunity to measure mobilization in mass protests, while simultaneously expanding the range of researchable questions. Location data not only improve estimation of the number and composition of participants in large demonstrations. Thanks to high spatial and temporal resolution they also reveal when, where, and with whom different sociopolitical sectors join a protest campaign. This article compares the features and advantages of this type of data with other methods of measuring who participates in street protests. The steps in preparing a usable data set are explained with reference to a six-week campaign of mass mobilization in Israel in 2011. Findings based on the Israeli data set illustrate a wide range of potential applications, pertaining to both the determinants and consequences of protest participation. Limitations of mobile location data and the privacy issues it raises are also discussed.
      Citation: Sociological Methods & Research
      PubDate: 2020-04-03T10:33:41Z
      DOI: 10.1177/0049124120914926
  • Intersectionality, Contextual Specificity, and Everyday Discrimination:
           Assessing the Difficulty Associated With Identifying a Main Reason for
           Discrimination Among Racial/Ethnic Minority Respondents
    • Authors: Catherine E. Harnois, João L. Bastos, Salma Shariff-Marco
      Abstract: Sociological Methods & Research, Ahead of Print.
      The Everyday Discrimination Scale is the most commonly used instrument to assess discrimination. The survey asks respondents about a range of negative interpersonal experiences and then asks them to provide a single main reason for all these experiences. Theories of intersectionality cast doubt on the idea that marginalized individuals generally perceive a single reason for the discrimination they encounter. We analyze data from 23 cognitive interviews with racial/ethnic minority adults to assess the degree of difficulty respondents have in assessing the main reason for their mistreatment, the sources of this difficulty, and potential consequences. Of the 21 respondents who reported experiencing some form of everyday discrimination, 43 percent encountered some difficulty in identifying a single main reason for their experiences; 42 percent of women who perceived some form of discrimination evidence significant frustration in identifying a main reason. Analyses show that, by requiring respondents to identify a single reason for their experiences of discrimination, the resulting data likely provide underestimates—and potentially biased estimates—of particular forms of discrimination.
      Citation: Sociological Methods & Research
      PubDate: 2020-03-30T10:43:07Z
      DOI: 10.1177/0049124120914929
  • What Can You Do With a Single Case' How to Think About Ethnographic
           Case Selection Like a Historical Sociologist
    • Authors: Josh Pacewicz
      Abstract: Sociological Methods & Research, Ahead of Print.
      Most social scientists agree that case studies are useful for “theory building,” but ethnographic methods papers often look to survey research for case selection strategies. This is due to a common but untenable distinction between theoretical and empirical generalization, which obscures how theoretically inclined ethnographers make implicit external validity claims. I analyze several exemplary ethnographies to show that (a) the distinction between theoretically and empirically oriented ethnography revolves around competing conventions for making claims that others accept as provisionally externally valid, (b) comparative-historical sociology provides a framework for evaluating how theoretically oriented ethnographies make such claims, and (c) each approach to making validity claims is optimized by different kinds of cases. Empirically oriented ethnographies make inductive claims via “pointy” cases wherein a phenomenon is pronounced or bifurcated. Theoretically oriented ethnographers are like post–Millian historical sociologist who triangulate past studies with resolutive or negative cases to make constitutive arguments.
      Citation: Sociological Methods & Research
      PubDate: 2020-02-13T10:43:13Z
      DOI: 10.1177/0049124119901213
  • The Age-Period-Cohort-Interaction Model for Describing and Investigating
           Inter-cohort Deviations and Intra-cohort Life-course Dynamics
    • Authors: Liying Luo, James S. Hodges
      Abstract: Sociological Methods & Research, Ahead of Print.
      Social scientists have frequently sought to understand the distinct effects of age, period, and cohort, but disaggregation of the three dimensions is difficult because cohort = period − age. We argue that this technical difficulty reflects a disconnection between how the cohort effect is conceptualized and how it is modeled in the traditional age-period-cohort framework. We propose a new method, called the age-period-cohort-interaction (APC-I) model, that is qualitatively different from previous methods in that it represents Ryder’s theoretical account about the conditions under which cohort differentiation may arise. This APC-I model does not require problematic statistical assumptions and the interpretation is straightforward. It quantifies inter-cohort deviations from the age and period main effects and also permits hypothesis testing about intra-cohort life-course dynamics. We demonstrate how this new model can be used to examine age, period, and cohort patterns in women’s labor force participation.
      Citation: Sociological Methods & Research
      PubDate: 2020-01-23T09:31:59Z
      DOI: 10.1177/0049124119882451
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