Analyzing Spatial Models of Choice and Judgment with R
Chapter 7: Advanced Topics
Code Files:
latent_RHS_model.bug:
JAGS/BUGS code that prevents the measurement model from conditioning on the predictive model, "cutting" the latent variable (Ideology).
summary.chainreg.r:
summary.chainreg function.
mimic_allvotes.r:
MIMIC model for all votes in the 111th House.
JAGS/BUGS code: mimic_allvotes.bug
mimic_keyvotes.r:
MIMIC model for only key votes in the 111th House.
JAGS/BUGS code: mimic_keyvotes.bug
mimic_keyvotes_plus_information.r:
MIMIC model for key votes plus legislator information in the 111th House.
JAGS/BUGS code: mimic_keyvotes_plus_information.bug
Dataset: H111.dta
ordinalIRT_ANES2004.r:
Runs ordinal IRT on issue scale data from the 2004 American National Election Study.
Dataset: ANES2004.Rda
dynamicIRT_ukcmp.r:
Runs dynamic IRT on UK manifesto data.
Dataset: uk_cmp_2012.dta
Supplemental Links:
MCMCpack for Bayesian Inference in R
Book Chapters
Analyzing Spatial Models of Choice and Judgment with R
Chapter 1: Introduction
Chapter 2: The Basics of R
Chapter 3: Analyzing Issue Scales
Chapter 4: Analyzing Similarities and Dissimilarities Data
Chapter 5: Unfolding Analysis of Rank Order and Ratio Scale Data
Chapter 6: Analyzing Legislative Roll Call (Binary Choice) Data
Chapter 7: Advance Topics
VOTEVIEW Blog
NOMINATE Data, Roll Call Data, and Software
Course Web Pages: University of Georgia (2010 - )
Course Web Pages: UC San Diego (2004 - 2010)
University of San Diego Law School (2005)
Course Web Pages: University of Houston (2000 - 2005)
Course Web Pages: Carnegie-Mellon University (1997 - 2000)
Analyzing Spatial Models of Choice and Judgment with R
Spatial Models of Parliamentary Voting
Recent Working Papers
Analyses of Recent Politics
About This Website
K7MOA Log Books: 1960 - 2017
Bio of Keith T. Poole
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