The focus of this book is on models for contingency table analysis. It deals mainly with log-
linear models and special models for ordinal data (log-linear or nonlinear). Special models …

Statistical models defined by imposing restrictions on marginal distributions of contingency
tables have received considerable attention recently. This paper introduces a general …

Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a
comprehensive overview of the basic principles of marginal modeling and offers a wide …

We analyze data from 927 remarried men and women to examine the association between
spouses' educational attainment, social class, and age in their first and current union …

The motivation for this book stems from the apparent lack of a general and flexible
methodology for testing hypotheses about relations among correlated categorical marginal …

This article examines changes in attitudes to gender roles in contemporary Britain by using a
first-order Markov process in which cumulative transition probabilities are logistic functions …

Growth data and longitudinal data in general are often of an ordinal nature. For example,
developmental stages may be classified into ordinal categories and behavioral variables …

This article presents a unifying approach to the analysis of repeated univariate categorical
(ordered) responses based on the application of the generalized log-linear modeling …

This paper proposes that idiographic graphical representations of psychological change
should complement psychometric test scores in the forensic context. In particular, it is argued …

Very often the data collected by social scientists involve dependent observations, without,
however, the investigators having any substantive interest in the nature of the …