Summarizes methods used for the analysis of categorical data, including many recently developed techniques. The emphasis is on loglinear and logit modeling techniques, which share many features with linear model methods for continuous variables. Incorporated into the exposition is interesting historical information (and controversies) on the development of categorical data analysis. Chapters 1-7 cover bivariate categorical data and loglinear and logit model building; chapters 8-11 discuss applications and methods; chapters 12 and 13 address theoretical foundations.
|Series:||Wiley Series in Probability and Statistics Series , #359|
|Product dimensions:||6.48(w) x 9.45(h) x 1.55(d)|
Table of Contents
Inference for Two-Way Contingency Tables.
Models for Binary Response Variables.
Fitting Loglinear and Logit Models.
Building and Applying Loglinear Models.
Loglinear-Logit Models for Ordinal Variables.
Multinomial Response Models.
Models for Matched Pairs.
Analyzing Repeated Categorical Response Data.
Asymptotic Theory for Parametric Models.
Estimation Theory for Parametric Models.
Index of Examples.
Index of Selected Notation.