A valuable overview of the most important ideas and results in statistical modeling Written by
a highly-experienced author, Foundations of Linear and Generalized Linear Models is a …

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 …

Capture-Recapture Methods for the Social and Medical Sciences Page 1 Page 2 Chapman &
Hall/CRC Interdisciplinary Statistics Series Edited by Dankmar Böhning Peter GM van der …

For the analysis of multivariate categorical longitudinal data, we propose an extension of the
dynamic logit model. The resulting model is based on a marginal parameterization of the …

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 provide a comprehensive overview of latent Markov (LM) models for the analysis of
longitudinal categorical data. The main assumption behind these models is that the …

We compare different selection criteria to choose the number of latent states of a multivariate
latent Markov model for longitudinal data. This model is based on an underlying Markov …

Acyclic directed mixed graphs (ADMGs) are graphs that contain directed (→) and bidirected
(↔) edges, subject to the constraint that there are no cycles of directed edges. Such graphs …

Marginal models involve restrictions on the conditional and marginal association structure of
a set of categorical variables. They generalize log-linear models for contingency tables …

Information-theoretic quantities reveal dependencies among variables in the structure of
joint, marginal, and conditional entropies while leaving certain fundamentally different …