Dynamic Patterns of Human Rights Practices

Abstract

A science of human rights requires valid comparisons of repression levels across time and space. Though extensive data collection efforts have made such comparisons possible in principle, statistical measures based on simple additive scales have made them rare in practice. This article uses a dynamic measurement model that contrasts with current approaches by (1) accounting for the fact that human rights indicators can be more or less informative about the latent level of repression, (2) allowing realistic descriptions of measurement uncertainty in the form of credible intervals, and (3) providing a theoretical motivation for modeling temporal dependence in human rights levels. We present several techniques, which demonstrate that the dynamic ordinal IRT model outperforms the static version of the model.

Keywords: human rights, data, IRT, dynamic measurement model, Bayesian statistics