We discuss two challenging scenarios for frequentist and/or Bayesian inference for categorical data. First, for parameter space regions described by order restrictions, frequentist methods are less straightforward than Bayesian methods, especially for interval estimation. Second, for marginal...

Though ubiquitous, Likert scaling’s traditional mode of analysis is often unable to uncover all of the valid information in a data set. Here, the authors discuss a solution to this problem based on methodology developed by quantum physicists: the state multipole method. The authors...

Nonparametric methods for matched pairs with data missing completely at random are considered. It is not assumed that the observations are coming from distribution functions belonging to a certain parametric or semi-parametric family. In particular, the distributions can have different shapes...

A large amount of data that is considered within sociological studies consists of categorical variables that lend themselves to tabular analysis. In the sociological analysis of data regarding social class and educational attainment, for example, the variables of interest can often plausibly be...