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Political Analysis Dataverse (Oxford Journals)
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Political Analysis is the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association. We publish articles that provide original and significant advances in the general area of political methodology, including both quantitative and qualitative methodological approaches.
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1 to 10 of 304 Results
Jun 9, 2017
Rohlfing, Ingo, 2017, "Replication Data for: Power and false negatives in Qualitative Comparative Analysis (QCA)", doi:10.7910/DVN/UNHYMP, Harvard Dataverse, V1, UNF:6:4QDrI2fEelRJmjDVYJ5hFw==
Files for reproducing figures and results in "Power and false negatives in Qualitative Comparative Analysis (QCA): Foundations, Simulation and Estimation for Empirical Studies"
May 25, 2017
Fachamps, Marcel ; Labonne, Julien, 2017, "Replication Data for "Using Split Samples to Improve Inference on Causal Effects"", doi:10.7910/DVN/Q0IXQY, Harvard Dataverse, V1
Replication Data for Fafchamps and Labonne (2017) "Using Split Samples to Improve Inference on Causal Effects"
May 11, 2017
Rosenberg, Andrew S.; Knuppe, Austin J.; Braumoeller, Bear F., 2017, "Replication Data for: Unifying the Study of Asymmetric Hypotheses", doi:10.7910/DVN/9NXGHP, Harvard Dataverse, V1, UNF:6:+SZmSIvjHdr1SOlsP0TKXQ==
This is a replication folder for “Unifying the Study of Asymmetric Hypotheses." This article presents a conceptual clarification of asymmetric hypotheses and a discussion of methodologies available to test them. Despite the existence of a litany of theories that posit asymmetric...
May 5, 2017
Cooperman, Alicia Dailey, 2017, "Replication Data for: Randomization Inference with Rainfall Data: Using Historical Weather Patterns for Variance Estimation", doi:10.7910/DVN/RJF61A, Harvard Dataverse, V1
This provides replication code and data for the paper "Randomization Inference with Rainfall Data: Using Historical Weather Patterns for Variance Estimation."
Apr 21, 2017
Morgan, Jason; Box-Steffensmeier, Janet M.; Christenson, Dino P., 2017, "Replication Data for: Modeling Unobserved Heterogeneity in Social Networks with the Frailty Exponential Random Graph Model", doi:10.7910/DVN/K3D1M2, Harvard Dataverse, V1
In the study of social processes, the presence of unobserved heterogeneity is a regular concern. It should be particularly worrisome for the statistical analysis of networks, given the complex dependencies that shape network formation combined with the re- strictive assumptions o...
Mar 26, 2017
Broockman, David; Kalla, Josh; Sekhon, Jasjeet, 2017, "Replication Data for: The Design of Field Experiments With Survey Outcomes: A Framework for Selecting More Efficient, Robust, and Ethical Designs", doi:10.7910/DVN/EEP5MT, Harvard Dataverse, V1, UNF:6:gM7KTUQ0wCS6voY98ZTw5A==
There is increasing interest in experiments where outcomes are measured by surveys and treat- ments are delivered by a separate mechanism in the real world, such as by mailers, door-to-door canvasses, phone calls, or online ads. However, common designs for such experiments are of...
Mar 15, 2017
Grimmer, Justin; Westwood, Sean; Messing, Solomon, 2017, "Replication Data for Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods", doi:10.7910/DVN/BQMLQW, Harvard Dataverse, V1, UNF:6:V/EzYnScVZ5qnN4UaU5ckQ==
This provides the replication code and data for the paper "Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods".
Feb 15, 2017
Jäger, Kai, 2017, "Replication Data for: The potential of online sampling for studying political activists around the world and across time", doi:10.7910/DVN/346Y30, Harvard Dataverse, V1, UNF:6:31jdPypumaMf7pceXHJInw==
Parties and social movements play an important role in many theories of political science. Yet, the study of intra-party politics remains underdeveloped as random samples are difficult to conduct among political activists. This paper proposes a novel procedure to sample different...
Feb 6, 2017
Rainey, Carlisle, 2017, "Replication Data for: Transformation-Induced Bias", doi:10.7910/DVN/CYXFB8, Harvard Dataverse, V1, UNF:6:XDVZ8wD2BMxScpCoFcCLYg==
Political scientists commonly focus on quantities of interest computed from model coefficients rather than on the coefficients themselves. However, the quantities of interest, such as predicted probabilities, first differences, and marginal effects, do necessarily not inherit the...
Jan 18, 2017
Heersink, Boris; Peterson, Brenton D.; Jenkins, Jeffery A., 2017, "Disasters and Elections: Estimating the Net Effect of Damage and Relief in Historical Perspective", doi:10.7910/DVN/AKHHHF, Harvard Dataverse, V1, UNF:6:bcCeuvD3haeNx4alZXnrWw==
Replication files for "Disasters and Elections: Estimating the Net Effect of Damage and Relief in Historical Perspective," by Boris Heersink, Brenton D. Peterson, and Jeffery A. Jenkins.
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