Loglinear models: A way to study main effects and interactions for multidimensional contingency tables with categorical data.

Until recently, behavioral researchers failed to examine categorical data based on multidimensional data in a unified whole because of the complex arithmetic such procedures entail. With the appearance of the loglinear model and user-friendly computer software, the problems associated with the analysis of multifaceted contingency tables no longer exist. In this article, we describe the loglinear model and apply it to categorical data cross-tabulated on four dimensions. We define contrasts similar to those of the analysis of variance and describe post hoc and planned comparison strategies. We illustrate hypothesis testing and model building for categorical data, and provide guidelines for performing an analysis on frequency data by using the loglinear model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)