Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences) - Softcover

John H. Aldrich; Forrest D. Nelson

Softcover

ISBN 10: 0803921330 ISBN 13: 9780803921337

Publisher: SAGE Publications, Inc, 1984

Synopsis

Ordinary regression analysis is not appropriate for investigating dichotomous or otherwise "limited" dependent variables, but this volume examines three techniques -- linear probability, probit, and logit models -- which are well-suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models. Using detailed examples, Aldrich and Nelson point out the differences among linear, logit, and probit models, and explain the assumptions associated with each.

About this title

About the Author:

John H. Aldrich is Pfizer-Pratt University Professor of Political Science at Duke University. He is author of Why Parties: A Second Look (2011), coeditor of Positive Changes in Political Science (2007), and author of Why Parties (1995) and Before the Convention (1980). He is a past president of both the Southern Political Science Association and the Midwest Political Science Association and is serving as president of the American Political Science Association. In 2001 he was elected a fellow in the American Academy of Arts and Sciences.

About this edition

• Publisher: SAGE Publications, Inc
• Publication date: 1984
• ISBN 10: 0803921330
• ISBN 13: 9780803921337
• Binding: Paperback
• Edition number: 1
• Number of pages: 96