Much of the theoretical literature on inequality assumes that the equalisand is a cardinal variable like income or wealth. However, health status is generally measured as a categorical variable expressing a qualitative order. Traditional solutions involve reclassifying the variable by means of...

Models with random effects/latent variables are widely used for capturing unobserved heterogeneity in multilevel/hierarchical data and account for associations in multivariate data. The estimation of those models becomes cumbersome as the number of latent variables increases due to...

The algorithm, generalized orthogonal components regression (GOCRE), is proposed to explore the relationship between a categorical outcome and a set of massive variables. A set of orthogonal components are sequentially constructed to account for the variation of the categorical outcome, and...

Antedependence (AD) of order p, also known as the Markov property of order p, is a property of index-ordered random variables in which each variable, given at least p immediately preceding variables, is independent of all further preceding variables. Zimmerman and Nunez-Anton (2010) present...

The purpose of this study was to investigate the performance of different approaches in analyzing multigroup multidimensional binary data under different conditions. Two multidimensional Item Response Theory (MIRT) methods (concurrent MIRT calibration and separate MIRT calibration with linking)...

Approaches to measuring health inequalities are often problematic in that they use methods that are inappropriate for categorical data. The approach here focuses on "pure" or univariate health inequality (rather than income-related or bivariate health inequality) and is based on a concept of...

This paper describes how to use the R package gateveys to establish a transparent and reproducible aggregation work flow for longitudinal data stemming from business tendency surveys (BTS). Business tendency survey researchers are addressed in particular though the suggested work flow could also...

This article reviews Regression Models for Categorical Dependent Variables Using Stata, Second Edition, by Long and Freese.

I. J. Good (1916 – 2009) was a prolific scientist who contributed to many fields, mostly from a Bayesian standpoint. This column explains his idea of quasi- Bayes (a.k.a. pseudo-Bayes) estimation or smoothing of categorical frequencies in a contingency table, which is especially useful as a...