Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation

摘要: Logistic regression models have been used in political science for estimating ideal points of legislators and Supreme Court justices. These present estimation identifiability challenges, such as improper variance estimates, scale translation invariance, reflection issues with outliers. We address these using Bayesian hierarchical modeling, linear transformations, informative predictors, explicit modeling In addition, we explore new ways to usefully display inferences check model fit.