The Analysis of Multivariate, Longitudinal Categorical Data by Log-Multilinear Models

The models developed in this thesis are designed to analyze the nature of the interactions present in 3-mode, multivariate, longitudinal categorical data. They are extensions of loglinear models that provide graphical representations of interactions or associations among discrete variables. The models are generalizations of association models for 2-way tables and are similar to canonical correlation models and their generalizations.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Anderson, Carolyn Jane

Contributors dc:contributor

• Wasserman, Stanley

• Statistics
• Psychology, Psychometrics

Identifier

(UMI)AAI9314836

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72118