Statistical Models for Repeated Categorical Ratings: The R package rater

A common occurrence in many disciplines is the need to assign a set of items into categories or classes with known labels. This is often done by one or more expert raters, or sometimes by an automated process. If these assignments, or 'ratings', are difficult to do, a common tactic is to repeat them by different raters, or even by the same rater multiple times on different occasions. We present an R package, rater, available on CRAN, that implements Bayesian versions of several statistical models that allow analysis of repeated categorical rating data. Inference is possible for the true underlying (latent) class of each item, as well as the accuracy of each rater. The models are based on, and include, the Dawid-Skene model, and we implemented them using the Stan probabilistic programming language. We illustrate usage of rater through a few examples. We also discuss in detail the techniques of marginalisation and conditioning, which are necessary for these models but also apply more generally to other models implemented in Stan.