Adaptive Tests for Ordered Categorical Data

Adaptive Tests for Ordered Categorical Data

Assessing Measurement Equivalence in Ordered-Categorical Data

Assessing measurement equivalence in the framework of the common factor linear models (CFL) is known as factorial invariance. This methodology is used to evaluate the equivalence among the parameters of a measurement model among different groups. However, when dichotomous, Likert, or ordered responses are used, one of the assumptions of the CFL is violated: the continuous nature of the observed...

A Generalized Linear Model for Repeated Ordered Categorical Response Data

We proposed a new approach to model longitudinal data consisting of transitional frequencies classified according to an ordered categorical response variable. Following an approach of Kalbfleisch and Lawless (1985), the responses are assumed to be sampled from an underlying continuous-time finite-state-space Markov chain, with the further assumption that direct transitions are strictly between ...

Elastic Net Constrained Stereotype Logit Model for Ordered Categorical Data

In biomedical studies the outcome of interest may be an ordinal, rather than a dichotomous, class label such as progression of disease. An example of an ordinal variable is drug toxicity levels evaluated as mild, moderate or severe. Another example is the Breast Imaging Reporting and Data System (BIRADS) [1] classification system. After a mammogram is read, a subjective score is assigned based ...

Graph-based Tests for Two-sample Comparisons of Categorical Data

We study the problem of two-sample comparison with categorical data when the contingency table is sparsely populated. In modern applications, the number of categories is often comparable to the sample size, causing existing methods to have low power. When the number of categories is large, there is often underlying structure on the sample space that can be exploited. We propose a general non-pa...