Bayesian Measurement Models for Analyzing Endorsement Experiments
Descriptive Plot of Endorsement Experiment Data
Fitting the Measurement Model of Political Support via Markov Chain Mo...
Counting Incidents around Points
Getting Indices of Incidents around a specified point
Predict Method for the Measurement Model of Political Support
Fit the hierarchical and non-hierarchical Bayesian measurement models proposed by Bullock, Imai, and Shapiro (2011) <DOI:10.1093/pan/mpr031> to analyze endorsement experiments. Endorsement experiments are a survey methodology for eliciting truthful responses to sensitive questions. This methodology is helpful when measuring support for socially sensitive political actors such as militant groups. The model is fitted with a Markov chain Monte Carlo algorithm and produces the output containing draws from the posterior distribution.