Linear Probability, Logit, And Probit Models (Quantitative Applications In The Social Sciences)
Publish Date: 1984-11-01
Author: John H. Aldrich;Forrest D. Nelson
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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.