Subjects -> MATHEMATICS (Total: 1013 journals)
    - APPLIED MATHEMATICS (92 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (714 journals)
    - MATHEMATICS (GENERAL) (45 journals)
    - NUMERICAL ANALYSIS (26 journals)
    - PROBABILITIES AND MATH STATISTICS (113 journals)

PROBABILITIES AND MATH STATISTICS (113 journals)                     

Showing 1 - 98 of 98 Journals sorted alphabetically
Advances in Statistics     Open Access   (Followers: 9)
Afrika Statistika     Open Access   (Followers: 1)
American Journal of Applied Mathematics and Statistics     Open Access   (Followers: 11)
American Journal of Mathematics and Statistics     Open Access   (Followers: 9)
Annals of Data Science     Hybrid Journal   (Followers: 14)
Annual Review of Statistics and Its Application     Full-text available via subscription   (Followers: 7)
Applied Medical Informatics     Open Access   (Followers: 11)
Asian Journal of Mathematics & Statistics     Open Access   (Followers: 8)
Asian Journal of Probability and Statistics     Open Access  
Austrian Journal of Statistics     Open Access   (Followers: 4)
Biostatistics & Epidemiology     Hybrid Journal   (Followers: 4)
Cadernos do IME : Série Estatística     Open Access  
Calcutta Statistical Association Bulletin     Hybrid Journal  
Communications in Mathematics and Statistics     Hybrid Journal   (Followers: 4)
Communications in Statistics - Simulation and Computation     Hybrid Journal   (Followers: 9)
Communications in Statistics: Case Studies, Data Analysis and Applications     Hybrid Journal  
Comunicaciones en Estadística     Open Access  
Econometrics and Statistics     Hybrid Journal   (Followers: 1)
Forecasting     Open Access   (Followers: 1)
Foundations and Trends® in Optimization     Full-text available via subscription   (Followers: 3)
Frontiers in Applied Mathematics and Statistics     Open Access   (Followers: 1)
Game Theory     Open Access   (Followers: 2)
Geoinformatics & Geostatistics     Hybrid Journal   (Followers: 14)
Geomatics, Natural Hazards and Risk     Open Access   (Followers: 13)
Indonesian Journal of Applied Statistics     Open Access  
International Game Theory Review     Hybrid Journal   (Followers: 1)
International Journal of Advanced Statistics and IT&C for Economics and Life Sciences     Open Access  
International Journal of Advanced Statistics and Probability     Open Access   (Followers: 7)
International Journal of Algebra and Statistics     Open Access   (Followers: 3)
International Journal of Applied Mathematics and Statistics     Full-text available via subscription   (Followers: 3)
International Journal of Ecological Economics and Statistics     Full-text available via subscription   (Followers: 4)
International Journal of Energy and Statistics     Hybrid Journal   (Followers: 3)
International Journal of Game Theory     Hybrid Journal   (Followers: 3)
International Journal of Mathematics and Statistics     Full-text available via subscription   (Followers: 2)
International Journal of Multivariate Data Analysis     Hybrid Journal  
International Journal of Probability and Statistics     Open Access   (Followers: 4)
International Journal of Statistics & Economics     Full-text available via subscription   (Followers: 6)
International Journal of Statistics and Applications     Open Access   (Followers: 2)
International Journal of Statistics and Probability     Open Access   (Followers: 3)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 5)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Iraqi Journal of Statistical Sciences     Open Access  
Japanese Journal of Statistics and Data Science     Hybrid Journal  
Journal of Biometrics & Biostatistics     Open Access   (Followers: 4)
Journal of Cost Analysis and Parametrics     Hybrid Journal   (Followers: 5)
Journal of Environmental Statistics     Open Access   (Followers: 4)
Journal of Game Theory     Open Access   (Followers: 1)
Journal of Mathematical Economics and Finance     Full-text available via subscription  
Journal of Mathematics and Statistics Studies     Open Access  
Journal of Modern Applied Statistical Methods     Open Access   (Followers: 1)
Journal of Official Statistics     Open Access   (Followers: 2)
Journal of Quantitative Economics     Hybrid Journal  
Journal of Social and Economic Statistics     Open Access  
Journal of Statistical Theory and Practice     Hybrid Journal   (Followers: 2)
Journal of Statistics and Data Science Education     Open Access   (Followers: 2)
Journal of Survey Statistics and Methodology     Hybrid Journal   (Followers: 4)
Journal of the Indian Society for Probability and Statistics     Full-text available via subscription  
Jurnal Biometrika dan Kependudukan     Open Access  
Jurnal Ekonomi Kuantitatif Terapan     Open Access  
Jurnal Sains Matematika dan Statistika     Open Access  
Lietuvos Statistikos Darbai     Open Access  
Mathematics and Statistics     Open Access   (Followers: 2)
Methods, Data, Analyses     Open Access   (Followers: 1)
METRON     Hybrid Journal   (Followers: 1)
Nepalese Journal of Statistics     Open Access  
North American Actuarial Journal     Hybrid Journal   (Followers: 1)
Open Journal of Statistics     Open Access   (Followers: 3)
Open Mathematics, Statistics and Probability Journal     Open Access  
Pakistan Journal of Statistics and Operation Research     Open Access   (Followers: 1)
Physica A: Statistical Mechanics and its Applications     Hybrid Journal   (Followers: 6)
Probability, Uncertainty and Quantitative Risk     Open Access   (Followers: 2)
Ratio Mathematica     Open Access  
Research & Reviews : Journal of Statistics     Open Access   (Followers: 3)
Revista Brasileira de Biometria     Open Access  
Revista Colombiana de Estadística     Open Access  
RMS : Research in Mathematics & Statistics     Open Access  
Romanian Statistical Review     Open Access  
Sankhya B - Applied and Interdisciplinary Statistics     Hybrid Journal  
SIAM Journal on Mathematics of Data Science     Hybrid Journal   (Followers: 1)
SIAM/ASA Journal on Uncertainty Quantification     Hybrid Journal   (Followers: 2)
Spatial Statistics     Hybrid Journal   (Followers: 2)
Sri Lankan Journal of Applied Statistics     Open Access  
Stat     Hybrid Journal   (Followers: 1)
Stata Journal     Full-text available via subscription   (Followers: 8)
Statistica     Open Access   (Followers: 6)
Statistical Analysis and Data Mining     Hybrid Journal   (Followers: 23)
Statistical Theory and Related Fields     Hybrid Journal  
Statistics and Public Policy     Open Access   (Followers: 4)
Statistics in Transition New Series : An International Journal of the Polish Statistical Association     Open Access  
Statistics Research Letters     Open Access   (Followers: 1)
Statistics, Optimization & Information Computing     Open Access   (Followers: 3)
Stats     Open Access  
Synthesis Lectures on Mathematics and Statistics     Full-text available via subscription   (Followers: 1)
Theory of Probability and its Applications     Hybrid Journal   (Followers: 2)
Theory of Probability and Mathematical Statistics     Full-text available via subscription   (Followers: 2)
Turkish Journal of Forecasting     Open Access   (Followers: 1)
VARIANSI : Journal of Statistics and Its application on Teaching and Research     Open Access  
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal  

           

Similar Journals
Journal Cover
Journal of Survey Statistics and Methodology
Journal Prestige (SJR): 2.212
Citation Impact (citeScore): 1
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2325-0984 - ISSN (Online) 2325-0992
Published by Oxford University Press Homepage  [419 journals]
  • Measuring Skin Color: Consistency, Comparability, and Meaningfulness of
           Rating Scale Scores and Handheld Device Readings

    • Free pre-print version: Loading...

      Authors: Gordon R; Branigan A, Khan M, et al.
      Pages: 337 - 364
      Abstract: AbstractAs US society continues to diversify and calls for better measurements of racialized appearance increase, survey researchers need guidance about effective strategies for assessing skin color in field research. This study examined the consistency, comparability, and meaningfulness of the two most widely used skin tone rating scales (Massey–Martin and PERLA) and two portable and inexpensive handheld devices for skin color measurement (Nix colorimeter and Labby spectrophotometer). We collected data in person using these four instruments from forty-six college students selected to reflect a wide range of skin tones across four racial-ethnic groups (Asian, Black, Latinx, White). These college students, five study staff, and 459 adults from an online sample also rated forty stock photos, again selected for skin tone diversity. Our results—based on data collected under controlled conditions—demonstrate high consistency across raters and readings. The Massey–Martin and PERLA scale scores were highly linearly related to each other, although PERLA better differentiated among people with the lightest skin tones. The Nix and Labby darkness-to-lightness (L*) readings were likewise linearly related to each other and to the Massey–Martin and PERLA scores, in addition to showing expected variation within and between race ethnicities. In addition, darker Massey–Martin and PERLA ratings correlated with online raters’ expectations that a photographed person experienced greater discrimination. In contrast, the redness (a*) and yellowness (b*) undertones were highest in the mid-range of the rating scale scores and demonstrated greater overlap across race-ethnicities. Overall, each instrument showed sufficient consistency, comparability, and meaningfulness for use in field surveys when implemented soundly (e.g., not requiring memorization). However, PERLA might be preferred to Massey–Martin in studies representing individuals with the lightest skin tones, and handheld devices may be preferred to rating scales to reduce measurement error when studies could gather only a single rating.
      PubDate: Wed, 12 Jan 2022 00:00:00 GMT
      DOI: 10.1093/jssam/smab046
      Issue No: Vol. 10, No. 2 (2022)
       
  • On The Robustness Of Respondent-Driven Sampling Estimators To Measurement
           Error

    • Free pre-print version: Loading...

      Authors: Fellows I.
      Pages: 377 - 396
      Abstract: AbstractRespondent-driven sampling (RDS) is a popular method of conducting surveys in hard to reach populations where strong assumptions are required in order to make valid statistical inferences. In this paper we investigate the assumption that network degrees are measured accurately by the RDS survey and find that there is likely significant measurement error present in typical studies. We prove that most RDS estimators remain consistent under an imperfect measurement model with little to no added bias, though the variance of the estimators does increase.
      PubDate: Wed, 05 Jan 2022 00:00:00 GMT
      DOI: 10.1093/jssam/smab056
      Issue No: Vol. 10, No. 2 (2022)
       
  • Neighborhood Bootstrap for Respondent-Driven Sampling

    • Free pre-print version: Loading...

      Authors: Yauck M; Moodie E, Apelian H, et al.
      Pages: 419 - 438
      Abstract: AbstractRespondent-driven sampling (RDS) is a form of link-tracing sampling, a sampling technique used for “hard-to-reach” populations that aims to leverage individuals’ social relationships to reach potential participants. There is a growing interest in the estimation of uncertainty for RDS as recent findings suggest that most variance estimators underestimate variability. Recently, Baraff et al. proposed the tree bootstrap method based on resampling the RDS recruitment tree, and empirically showed that this method outperforms current bootstrap methods. However, some findings suggest that the tree bootstrap (severely) overestimates uncertainty. In this article, we propose the neighborhood bootstrap method for quantifying uncertainty in RDS. We prove the consistency of our method under some conditions and investigate its finite sample performance, through a simulation study, under realistic RDS sampling assumptions.
      PubDate: Sat, 26 Feb 2022 00:00:00 GMT
      DOI: 10.1093/jssam/smab057
      Issue No: Vol. 10, No. 2 (2022)
       
  • Erratum to: On The Robustness Of Respondent-Driven Sampling Estimators To
           Measurement Error

    • Free pre-print version: Loading...

      Authors: Fellows I.
      Pages: 489 - 489
      Abstract: Journal of Survey Statistics and Methodology, smab056, https://doi.org/10.1093/jssam/smab056
      PubDate: Fri, 11 Mar 2022 00:00:00 GMT
      DOI: 10.1093/jssam/smac004
      Issue No: Vol. 10, No. 2 (2022)
       
  • Positive Learning or Deviant Interviewing' Mechanisms of Experience on
           Interviewer Behavior

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      Authors: Kosyakova Y; Olbrich L, Sakshaug J, et al.
      Pages: 249 - 275
      Abstract: AbstractInterviewer (mis)behavior has been shown to change with interviewers’ professional experience (general experience) and experience gained during the field period (survey experience). We extend this study by using both types of experiences to analyze interviewer effects on a core quality indicator: interview duration. To understand whether the effect of interviewer experience on duration is driven by increased efficiency or deviant behavior—both mechanisms of shorter interview durations—we additionally examine the triggering rate of filter questions to avoid burdensome follow-up questions and response differentiation over the field period. Using multilevel models and data from a large-scale survey on a special and difficult-to-interview population of refugees in Germany, we find that interview duration decreases with increasing survey experience, particularly among the generally inexperienced interviewers. However, this effect is not found for the triggering rate and response differentiation. The results are robust to different sample and model specifications. We conclude that the underlying mechanism driving interview duration is related to increasing efficiency, and not deviant behavior.
      PubDate: Mon, 22 Feb 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab003
      Issue No: Vol. 10, No. 2 (2021)
       
  • Examining Interviewers’ Ratings of Respondents’ Health: Does Location
           in the Survey Matter for Interviewers’ Evaluations of Respondents'

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      Authors: Garbarski D; Schaeffer N, Dykema J.
      Pages: 276 - 298
      Abstract: AbstractInterviewers’ ratings of survey respondents’ health (IRH) are a promising measure of health to include in surveys as a complementary measure to self-rated health. However, our understanding of the factors contributing to IRH remains incomplete. This is the first study to examine whether and how it matters when in the interview interviewers evaluate respondents’ health in a face-to-face survey, in an experiment embedded in the UK Innovation Panel Study. We find that interviewers are more likely to rate the respondent’s health as “excellent” when IRH is rated at the end of the interview compared to the beginning. Drawing from the continuum model of impression formation, we examined whether associations between IRH and relevant covariates vary depending on placement in interview. We find that across several characteristics of interviewers and respondents, only the number of interviews completed by interviewers varies by IRH assessment location in its effect on IRH. We also find evidence that interviewer variance is lower when IRH is assessed prior to compared to after the interview. Finally, the location of IRH assessment does not impact the concurrent or predictive validity of IRH. Overall, the results suggest that in a general population study with some health questions, there may be benefits to having interviewers rate respondents’ health at the beginning of the interview (rather than at the end as in prior research) in terms of lower interviewer variance, particularly in the absence of interviewer training that mitigates the impact of within-study experience on IRH assessments.
      PubDate: Wed, 13 Oct 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab025
      Issue No: Vol. 10, No. 2 (2021)
       
  • Interviewer Effects in Live Video and Prerecorded Video Interviewing

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      Authors: West B; Ong A, Conrad F, et al.
      Pages: 317 - 336
      Abstract: AbstractLive video (LV) communication tools (e.g., Zoom) have the potential to provide survey researchers with many of the benefits of in-person interviewing, while also greatly reducing data collection costs, given that interviewers do not need to travel and make in-person visits to sampled households. The COVID-19 pandemic has exposed the vulnerability of in-person data collection to public health crises, forcing survey researchers to explore remote data collection modes—such as LV interviewing—that seem likely to yield high-quality data without in-person interaction. Given the potential benefits of these technologies, the operational and methodological aspects of video interviewing have started to receive research attention from survey methodologists. Although it is remote, video interviewing still involves respondent–interviewer interaction that introduces the possibility of interviewer effects. No research to date has evaluated this potential threat to the quality of the data collected in video interviews. This research note presents an evaluation of interviewer effects in a recent experimental study of alternative approaches to video interviewing including both LV interviewing and the use of prerecorded videos of the same interviewers asking questions embedded in a web survey (“prerecorded video” interviewing). We find little evidence of significant interviewer effects when using these two approaches, which is a promising result. We also find that when interviewer effects were present, they tended to be slightly larger in the LV approach as would be expected in light of its being an interactive approach. We conclude with a discussion of the implications of these findings for future research using video interviewing.
      PubDate: Fri, 03 Dec 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab040
      Issue No: Vol. 10, No. 2 (2021)
       
  • A Model-Assisted Approach for Finding Coding Errors in Manual Coding of
           Open-Ended Questions

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      Authors: He Z; Schonlau M.
      Pages: 365 - 376
      Abstract: AbstractText answers to open-ended questions are typically manually coded into one of several codes. Usually, a random subset of text answers is double-coded to assess intercoder reliability, but most of the data remain single-coded. Any disagreement between the two coders points to an error by one of the coders. When the budget allows double coding additional text answers, we propose employing statistical learning models to predict which single-coded answers have a high risk of a coding error. Specifically, we train a model on the double-coded random subset and predict the probability that the single-coded codes are correct. Then, text answers with the highest risk are double-coded to verify. In experiments with three data sets, we found that this method identifies two to three times as many coding errors in the additional text answers as compared to random guessing, on average. We conclude that this method is preferred if the budget permits additional double-coding. When there are a lot of intercoder disagreements, the benefit can be substantial.
      PubDate: Tue, 03 Aug 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab022
      Issue No: Vol. 10, No. 2 (2021)
       
  • Estimating the Size and Distribution of Networked Populations with
           Snowball Sampling

    • Free pre-print version: Loading...

      Authors: Vincent K; Thompson S.
      Pages: 397 - 418
      Abstract: AbstractA new strategy is introduced for estimating population size and networked population characteristics. Sample selection is based on a multi-wave snowball sampling design. A generalized stochastic block model is posited for the population’s network graph. Inference is based on a Bayesian data augmentation procedure. Applications are provided to simulated populations and an empirical population. The results demonstrate that statistically efficient estimates of the size and distribution of the population can be achieved.
      PubDate: Sat, 17 Jul 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smaa042
      Issue No: Vol. 10, No. 2 (2021)
       
  • Model-Based Inference for Rare and Clustered Populations From Adaptive
           Cluster Sampling Using Auxiliary Variables

    • Free pre-print version: Loading...

      Authors: Nolau I; Gonçalves K, Pereira J.
      Pages: 439 - 465
      Abstract: AbstractRare populations, such as endangered animals and plants, drug users and individuals with rare diseases, tend to cluster in regions. Adaptive cluster sampling is generally applied to obtain information from clustered and sparse populations since it increases survey effort in areas where the individuals of interest are observed. This work proposes a unit-level model which assumes that counts are related to auxiliary variables, improving the sampling process by assigning different weights to the cells, besides referring to them spatially. The proposed model fits rare and grouped populations arranged on a regular grid in a Bayesian framework. The approach is compared to alternative methods using simulated data and a real experiment in which adaptive samples were drawn from an African buffalo population in a 24,108 square kilometer area in East Africa. Simulation studies show that the model is efficient in several settings, validating the method proposed in this paper for practical situations.
      PubDate: Fri, 05 Feb 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab001
      Issue No: Vol. 10, No. 2 (2021)
       
  • Challenges of Virtual RDS for Recruitment of Sexual Minority Women for a
           Behavioral Health Study

    • Free pre-print version: Loading...

      Authors: Middleton D; Drabble L, Krug D, et al.
      Pages: 466 - 488
      Abstract: AbstractRespondent-driven sampling (RDS) is an approach commonly used to recruit nonprobability samples of rare and hard-to-find populations. The purpose of this study was to explore the utility of phone- and web-based RDS methodology to sample sexual minority women (SMW) for participation in a telephone survey. Key features included (i) utilizing a national probability survey sample to select seeds; (ii) web-based recruitment with emailed coupons; and (iii) virtual processes for orienting, screening, and scheduling potential participants for computer-assisted telephone interviews. Rather than resulting in a large diverse sample of SMW, only a small group of randomly selected women completed the survey and agreed to recruit their peers, and very few women recruited even one participant. Only seeds from the most recent of two waves of the probability study generated new SMW recruits. Three RDS attempts to recruit SMW over several years and findings from brief qualitative interviews revealed four key challenges to successful phone- and web-based RDS with this population. First, population-based sampling precludes sampling based on participant characteristics that are often used in RDS. Second, methods that distance prospective participants from the research team may impede development of relationships, investment in the study, and motivation to participate. Third, recruitment for telephone surveys may be impeded by multiple burdens on seeds and recruits (e.g., survey length, understanding the study and RDS process). Finally, many seeds from a population-based sample may be needed, which is not generally feasible when working with a limited pool of potential seeds. This method may yield short recruitment chains, which would not meet key RDS assumptions for approximation of a probability sample. In conclusion, potential challenges to using RDS in studies with SMW, particularly those using virtual approaches, should be considered.
      PubDate: Wed, 06 Oct 2021 00:00:00 GMT
      DOI: 10.1093/jssam/smab039
      Issue No: Vol. 10, No. 2 (2021)
       
  • The Carryover Effects of Preceding Interviewer–Respondent Interaction on
           Responses in Audio Computer-Assisted Self-Interviewing (ACASI)

    • Free pre-print version: Loading...

      Authors: Sun H; Conrad F, Kreuter F.
      Pages: 299 - 316
      Abstract: AbstractAudio computer-assisted self-interviewing (ACASI) has been widely used to collect sensitive information from respondents in face-to-face interviews. Interviewers ask questions that are not sensitive or only moderately sensitive and then allow respondents to self-administer more sensitive questions, listening to audio recordings of the questions and typically entering their responses directly into the same device that the interviewer has used. According to the conventional thinking, ACASI is taken as independent of the face-to-face interaction that almost always precedes it. Presumably as a result of this presumed independence, the respondents’ prior interaction with the interviewer is rarely considered when assessing the quality of ACASI responses. There is no body of existing research that has experimentally investigated how the preceding interviewer–respondent interaction may create sufficient social presence to affect responses in the subsequent ACASI module. The study reported here, a laboratory experiment with eight professional interviewers and 125 respondents, explores the carryover effects of preceding interactions between interviewer and respondent on responses in the subsequent ACASI. We evaluated the impact of the similarity of the live and recorded interviewer’s voice for each respondent as well as respondents’ rapport with interviewers in the preceding interview. We did not find significant main effects of vocal similarity on disclosure in ACASI. However, we found significant interaction effects between vocal similarity and respondents’ rapport ratings in the preceding interview on disclosure in ACASI. When the ACASI voice was similar to the interviewer’s voice in the preceding interaction, respondent-rated rapport led to more disclosure but, when the ACASI voice is clearly different from the interviewer’s voice, respondent-rated rapport in the prior interaction did not affect disclosure.
      PubDate: Thu, 03 Dec 2020 00:00:00 GMT
      DOI: 10.1093/jssam/smaa019
      Issue No: Vol. 10, No. 2 (2020)
       
 
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