I checked 7 public opinion journals on Wednesday, May 06, 2026 using the Crossref API. For the period April 29 to May 05, I found 8 new paper(s) in 4 journal(s).

Journal of Elections, Public Opinion and Parties

Why survey turnout data misleads: probing, selection bias, and misinterpreted political participation
Kasper M. Hansen
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The conditional value of legislative effectiveness
Elizabeth N. Simas
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Journal of Official Statistics

Assessing the Heterogeneity in Mode Effects on Data Quality, Response Distributions, and Future Participation Across Sociodemographic Subgroups in a Mixed-Mode Panel Study
Heather M. Schroeder, Mary Beth Ofstedal, Brady T. West
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Introducing a web option in interviewer-administered surveys could increase response rates and reduce costs. However, this requires careful assessment of the effects of mixed-mode designs on data quality and key measures, especially across important sociodemographic subgroups. In 2018 and 2020, the Health and Retirement Study (HRS) experimentally introduced web in a sequential mixed-mode design for panelists assigned to the telephone mode. Initial analyses found a limited number of mode effects on key outcome distributions and data quality measures. This paper extends this initial analysis by assessing possible heterogeneity in these effects among sociodemographic subgroups defined by race/ethnicity, sex, and others. We interact mode with each sociodemographic indicator in statistical models for each outcome. Overall, we found limited evidence of heterogeneity in the mode effects, with 3% of the 204 interaction terms we tested emerging as significant. For example, previous work showed that more household roster changes are reported in the web-first group, and we found that this was more pronounced for females and those with some college education. Although some heterogeneity in mode effects was observed across subgroups, the effects were generally too small to cause data quality concerns. We conclude with a discussion of broader considerations for survey researchers.
Comparison of Small Area Procedures Based on Gamma Distributions with Extension to Informative Sampling
Yanghyeon Cho, Emily Berg
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The gamma distribution is a useful model for small area prediction of a skewed response variable. We study the use of the gamma distribution for small area prediction. We emphasize a model, called the gamma-gamma model, in which the area random effects have gamma distributions. We compare this model to a generalized linear mixed model. Each of these two models has been proposed independently in the literature, but the two models have not yet been formally compared. We evaluate the properties of two mean square error estimators for the gamma-gamma model, both of which incorporate corrections for the bias of the estimator of the leading term. Finally, we extend the gamma-gamma model to informative sampling. We conduct thorough simulation studies to assess the properties of the alternative predictors. We apply the proposed methods to data from an agricultural survey.
Geographical Rezoning as a Combinatorial Game: Case Study of the Australian Statistical Geography Standard
Filip Juricev-Martincev, Helen Thompson, Gentry White
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Geographical rezoning is a combinatorial optimization problem of assigning basic spatial units into regions for statistical analysis and the publication of official government statistics, such as the Census. We propose a novel approach by reframing this problem into a single-player, deterministic, fully-informative, finite combinatorial game; or simply, a single-player puzzle. This definition allows effective and systematic exploration of state-space, and offers perfect information guarantees, as well as decouples the problem definition from a specific solver algorithm. We take an existing combinatorial algorithm called HeLP (Hierarchical Land Parcel Aggregation), and combine its rezoning heuristic with a game-playing algorithm, Monte Carlo tree search, to create three new game-playing solvers for the geographical rezoning problem. A case study was conducted on a real-world data set in Canberra, Australia, on the Australian Statistical Geography Standard (ASGS). Our Monte Carlo implementations, HeLP-MCTS, HeLP-RAVE, and HeLP-RHEA, were tested on simulated data and have yielded a 50.25%, 28.77%, and 57.02% increase in the mean value of the partitioning heuristic function, respectively, compared to a combinatorial solver HeLP. We have also computationally improved the original HeLP algorithm, offering significant speed increases.

Journal of Survey Statistics and Methodology

SCREEN RESOLUTION AND QR CODES IN PUSH-TO-WEB SURVEYS: A QUICK RESPONSE TO SURVEY BREAKOFF?
Katharina Pfaff, Christina Walcherberger
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The integration of QR codes (quick response codes) in web surveys has become commonplace, aimed at simplifying survey access for respondents using mobile devices. While previous studies have presented mixed findings regarding the effectiveness of QR codes in enhancing survey participation, this research re-examines their impact on survey breakoff, identifying potential explanatory factors such as the screen resolution of the respondent’s device. Drawing on data from the Digitize! Online Panel Survey, a probability sample of up to 1,228 respondents in Austria, this study uses an exploratory research design to investigate how screen resolution, QR code usage, and frequency of personal computer or mobile device use influence survey breakoff behavior. We find that QR code utilization alone does not significantly predict survey breakoff once other covariates are accounted for. However, the resolution of the device used for the survey emerges as a critical determinant, with higher resolutions associated with lower probability of survey breakoff. The study thus uncovers a nuanced relationship between screen resolution and survey breakoff, particularly noticeable when transitioning from mobile devices likely to be smaller, such as smartphones, to those with larger screens, like tablets. While QR codes offer convenience and accessibility advantages, their implementation requires careful consideration to mitigate potential drawbacks and optimize survey engagement. Overall, this study contributes valuable insights into the evolving landscape of digital survey methodologies, highlighting avenues for future research to enhance data validity and reliability.
Improving the Measurement of Gender in Surveys: Effects of Select-One or Select-all-that-Apply Response Format on Measurement and Data Quality Among College Students
Dana Garbarski, Jennifer Dykema, James A Yonker, Rosie Eungyuhl Bae, Michael Topping
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Recent guidelines on the measurement of gender in surveys recommend a two-step strategy that asks about sex assigned at birth followed by current gender identity using a small number of offered response categories (e.g., female, male, transgender) and an open response field to capture any residual categories (“not listed, please tell us”). However, more research on several fronts is needed to continue to refine our measurement strategies across contexts, and this work continues to be critically important with the dismantling of federally funded research regarding gender identity. In the current study, we examine the impact of response format on the measurement of gender identity. This study reports results from a between-subjects experiment embedded in a campus climate survey about inclusion and belonging at a large Midwestern university in Fall 2024. Over 16,000 students were asked, “What is your gender?” and subsequently randomly assigned to respond using one of two response formats. The first allowed respondents to “select-one” of the response options “woman, man, nonbinary, not listed (please tell us),” and was followed by the question “Are you transgender? Yes/No.” The second included the response options “woman, man, nonbinary, transgender, not listed (please tell us)” and instructed respondents to “select all that apply.” We examine the distribution of responses, item nonresponse, the number of gender categories reported, response times, and concurrent validity (in terms of the association between gender and survey outcomes about campus climate) across the two formats. While the results mainly show similarities in outcomes between the response formats, respondents are more likely to indicate they are transgender in the “select-one” format. By contrast, respondents are more likely to indicate gender expansiveness other than “transgender” or “nonbinary” with the “select-all” format. We discuss the implications of these findings for future research.

Politics, Groups, and Identities

Anti-Indigenous attitudes and divided support: the Indigenous voice and public opinion in Australia
Raymond Foxworth, Carew Boulding, Sarah Maddison, Edana Beauvais
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