1 to 10 of 12 Results
Jan 28, 2013
Jeff Gill and Christopher Witko, 2013, "Bayesian Analytical Methods: A Methodological Prescription for Public Administration", https://doi.org/10.7910/DVN/OHMA5H, Harvard Dataverse, V1
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May 30, 2011
Jeff Gill, 2011, "Replication data for: One Year and Four Elections: A Study of the 1998 Capps Campaign for California's 22nd District.", https://doi.org/10.7910/DVN/6TSERS, Harvard Dataverse, V2
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May 30, 2011
Jeff Gill, 2011, "Replication data for: Critical Differences in Bayesian and Non-Bayesian Inference and Why the Former is Better.", https://doi.org/10.7910/DVN/NECZTX, Harvard Dataverse, V2
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May 30, 2011
Kevin Wagner; Jeff Gill, 2011, "Replication data for: Bayesian Inference in Public Administration Research: Substantive Differences from Somewhat Different Assumptions.", https://doi.org/10.7910/DVN/2DFAD0, Harvard Dataverse, V2
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May 30, 2011
Minjung Kyung; Jeff Gill; George Casella, 2011, "Replication data for: "Sampling Schemes for Generalized Linear Dirichlet Process Random Effects Models."", https://doi.org/10.7910/DVN/XBF8P7, Harvard Dataverse, V4
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May 30, 2011
Chris Zorn; Jeff Gill, 2011, "Replication data for: The Etiology of Public Support for the Designated Hitter Rule", https://doi.org/10.7910/DVN/Q6VJR7, Harvard Dataverse, V2, UNF:5:xUzBJfbVX0x7FBlFkqPhOQ== [fileUNF]
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May 24, 2011
Jeff Gill, 2011, "Replication data for: An Entropy Measure of Uncertainty in Vote Choice", https://doi.org/10.7910/DVN/TMRABS, Harvard Dataverse, V2
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May 24, 2011
Jeff Gill; Donimik Hangartner, 2011, "Replication data for: Circular Data in Political Science and How to Handle It.", https://doi.org/10.7910/DVN/9R1YAK, Harvard Dataverse, V3, UNF:5:hP6yk4Ocnr5JZWV+bwF/GA== [fileUNF]
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May 8, 2011
Jeff Gill; Gary King, 2011, "Replication data for: What to do When Your Hessian is Not Invertible: Alternatives to Model Respecification in Nonlinear Estimation."", https://doi.org/10.7910/DVN/0LRZN6, Harvard Dataverse, V1
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May 8, 2011
Jeff Gill; George Casella, 2011, "Replication data for: Nonparametric Priors For Ordinal Bayesian Social Science Models: Specification and Estimation", https://doi.org/10.7910/DVN/1BJQVW, Harvard Dataverse, V1
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