21 to 30 of 586 Results
Dec 5, 2024
Velez, Yamil, 2024, "Replication Data for Crowdsourced Adaptive Surveys", https://doi.org/10.7910/DVN/QVOLDN, Harvard Dataverse, V1, UNF:6:3MWn5WLKmcM3f1hANpHaUw== [fileUNF]
Public opinion surveys are vital for informing democratic decision-making, but responding to rapidly evolving information environments and measuring beliefs within niche communities can be challenging for traditional survey methods. This paper introduces a crowdsourced adaptive survey methodology (CSAS) that unites advances in natural language proc... |
Dec 5, 2024
Binding, Garret; Koc, Piotr, 2024, "Replication Data for: Adding Regularized Horseshoes to the Dynamics of Latent Variable Models", https://doi.org/10.7910/DVN/G2VRQH, Harvard Dataverse, V1
Dynamic latent variable models generally link units' positions on a latent dimension over time via random walks. Theoretically, these trajectories are often expected to resemble a mixture of periods of stability interrupted by moments of change. In these cases, a prior distribution such as the regularized horseshoe---that allows for both stasis and... |
Halterman, Andrew, 2024, "Replication Data for: Synthetically generated text for supervised text analysis", https://doi.org/10.7910/DVN/JJ5BBX, Harvard Dataverse, V1, UNF:6:JJUrUpeMWFKHndQZmjKvEw== [fileUNF]
Large language models are a powerful tool for conducting text analysis in political science, but using them to annotate text has several drawbacks, including high cost, limited reproducibility, and poor explainability. Traditional supervised text classifiers are fast and reproducible, but require expensive hand annotation, which is especially diffi... |
Armstrong II, David A.; Poirier, William, 2024, "Replication Data for: Decoupling Visualization and Testing when Presenting Confidence Intervals", https://doi.org/10.7910/DVN/GFLSLH, Harvard Dataverse, V1, UNF:6:7YwBZigHqeniuWXi2e77lQ== [fileUNF]
Confidence intervals are ubiquitous in the presentation of social science models, data, and effects. When several intervals are plotted together, one natural inclination is to ask whether the estimates represented by those intervals are significantly different from each other. Unfortunately, there is no general rule or procedure that would allow us... |
Nov 14, 2024
Bansak, Kirk; Jenke, Libby, 2024, "Replication Materials for: Odd Profiles in Conjoint Experimental Designs: Effects on Survey-Taking Attention and Behavior", https://doi.org/10.7910/DVN/6PXYGY, Harvard Dataverse, V1
This repository contains replication materials for the study, "Odd Profiles in Conjoint Experimental Designs: Effects on Survey-Taking Attention and Behavior" in Political Analysis. See the readme.txt for details. |
Nov 9, 2024
Berwick, Elissa; Caughey, Devin, 2024, "Replication Data for: Berwick and Caughey, "MODGIRT: Multidimensional Dynamic Scaling of Aggregate Survey Data"", https://doi.org/10.7910/DVN/UUPSCM, Harvard Dataverse, V1
Each of the four applications in the paper and supplemental materials has a separate compressed directory. Each directory is a self-contained capsule with its own README, input data, R code, and intermediate output. Unzip application directories to replicate analysis. |
Nov 7, 2024
Schulz, William, 2024, "Replication Materials for "What Would You Say? Estimating Causal Effects of Social Context on Political Expression"", https://doi.org/10.7910/DVN/GBSOAS, Harvard Dataverse, V1
This capsule contains all materials needed to replicate results presented in the paper "What Would You Say? Estimating Causal Effects of Social Context on Political Expression" by William Small Schulz. The results can be reproduced by running the code/analyses.R script, which will output all analyses presented in the paper. The file metadata/file_n... |
Nov 4, 2024
Hill, Seth J.; Roberts, Margaret E., 2022, "Replication Data for: Acquiescence Bias Inflates Estimates of Conspiratorial Beliefs and Political Misperceptions", https://doi.org/10.7910/DVN/TVJCTX, Harvard Dataverse, V2
Scholars, pundits, and politicians use opinion surveys to study citizen beliefs about political facts, such as the current unemployment rate, and more conspiratorial beliefs, such as whether Barack Obama was born abroad. Many studies, however, ignore acquiescence-response bias, the tendency for survey respondents to endorse any assertion made in a... |
Oct 30, 2024
Kim, Seo-young Silvia; Atsusaka, Yuki, 2024, "Replication Data for: Addressing Measurement Errors in Ranking Questions for the Social Sciences", https://doi.org/10.7910/DVN/UCTXEF, Harvard Dataverse, V1
Social scientists often use ranking questions to study people's opinions and preferences. However, little is understood about the general nature of measurement errors in such questions, let alone their statistical consequences and what researchers can do about them. We introduce a statistical framework to improve ranking data analysis by addressing... |
Oct 30, 2024
Green, Breanna; Hobbs, William; Avila, Sofia; Rodriguez, Pedro; Spirling, Arthur; Stewart, Brandon, 2024, "Replication materials for: Measuring Distances in High Dimensional Spaces Why Average Group Vector Comparisons Exhibit Bias, And What to Do About it", https://doi.org/10.7910/DVN/YDNVSN, Harvard Dataverse, V1
Analysts often seek to compare representations in high-dimensional space, e.g. embedding vectors of the same word across groups. We show that the distance measures calculated in such cases can exhibit considerable statistical bias, that stems from uncertainty in the estimation of the elements of those vectors. This problem applies to Euclidean dist... |
