<p>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. </p>

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

Politics & Social Sciences

John H. Aldrich

Forrest D. Nelson

Social Sciences

Sage Publications, Inc.

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Books by Forrest D. Nelson

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