Using real-world data examples, this authoritative book shows how to use
the latest configural frequency analysis (CFA) techniques to analyze
categorical data. Some of the techniques are presented here for the
first time. In contrast to methods that focus on relationships among
variables, such as log-linear modeling, CFA allows researchers to
evaluate differences and change at the level of individual cells in a
table. Illustrated are ways to identify and test for cell configurations
that are either consistent with or contrary to hypothesized patterns
(the types and antitypes of CFA); control for potential covariates that
might influence observed results; develop innovative prediction models;
address questions of moderation and mediation; and analyze intensive
longitudinal data. The book also describes free software applications
for executing CFA.