Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation

Andrew Gelman Department of Statistics and Department of Political Science, Columbia University, New York, NY e-mail: gelman{at}stat.columbia.edu, www.stat.columbia.edu/~gelman/ David K. Park Department of Political Science, Washington University, St. Louis, MO e-mail: dpark{at}artsci.wustl.edu Noah Kaplan Department of Political Science, University of Houston, Houston, TX e-mail: nkaplan{at}uh.edu Logistic regression models have been used in political sciencefor estimating ideal points of legislators and Supreme Courtjustices. These models present estimation and identifiabilitychallenges, such as improper variance estimates, scale and translationinvariance, reflection invariance, and issues with outliers.We address these issues using Bayesian hierarchical modeling,linear transformations, informative regression predictors, andexplicit modeling for outliers. In addition, we explore newways to usefully display inferences and check model fit.     

The developmental parameters of relative deprivation theory

Studies in Comparative International Development -     

Perspective and procedural justice: Attorney and litigant evaluations of court procedures

A comparison of the procedural justice judgments of attorneys and those of lay people judging the same procedures offers an opportunity to generate new information on what factors affect judgments of fairness. In a survey of reactions to conventional and innovative procedures in a United States district court, attorneys and lay people involved in tort and contract cases were asked to judge the overall fairness of court procedures and the fairness of specific procedures used in arbitration hearings. The respondents were also asked for their judgments concerning the favorability of the procedure's outcome, the opportunity to have the case heard and decided by an impartial third party, and their side's control over what happened in the case, all of which are factors found in previous studies to affect procedural fairness judgments. The results showed that, while attorneys gave higher overall fairness ratings than did litigants, the difference was not affected by the procedure assigned to the case. In addition, attorneys and litigants appeared to use the same standards to evaluate the fairness of procedures, although they disagreed about where the procedures they experienced fell on these dimensions. The theoretical and practical implications of the results are discussed.     

Reassessing Schoenfeld Residual Tests of Proportional Hazards in Political Science Event History Analyses

An underlying assumption of proportional hazards models is that the effect of a change in a covariate on the hazard rate of event occurrence is constant over time. For scholars using the Cox model, a Schoenfeld residual‐based test has become the disciplinary standard for detecting violations of this assumption. However, using this test requires researchers to make a choice about a transformation of the time scale. In practice, this choice has largely consisted of arbitrary decisions made without justification. Using replications and simulations, we demonstrate that the decision about time transformations can have profound implications for the conclusions reached. In particular, we show that researchers can make far more informed decisions by paying closer attention to the presence of outlier survival times and levels of censoring in their data. We suggest a new standard for best practices in Cox diagnostics that buttresses the current standard with in‐depth exploratory data analysis.