Logit Modeling

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Alfred DeMaris - Bowling Green State University, Ohio, USA

Volume: 86

Series:
Quantitative Applications in the Social Sciences

Other Titles in:
Quantitative/Statistical Research (General) | Regression & Correlation | Research Methods in Psychology

July 1992 | 96 pages | SAGE Publications, Inc

Description
Contents

Logit modelling represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, particularly whenever the measurement assumptions for classical multiple regression fail to be met. Taking an applied approach, DeMaris begins by describing the logit model in the context of the general loglinear model, moving its application from two-way to multidimensional tables. He then divides the rest of the book between an examination of the varieties of logit models for contingency tables and logistic regression. Throughout his coverage of both these major areas, DeMaris emphasizes interpretation of results. The book concludes with an extension of logistic regression to dependent variables with more than two categories.

Introduction

Logit Models

Theoretical Background

Logit Models for Multidimensional Tables

Logistic Regression

Advanced Topics in Logistic Regression

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