After showing why ordinary regression analysis is not appropriate for investigating dichotomous or otherwise "limited" dependent variables, 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 between linear, logit, and probit models, and explain the assumptions. Economists, as well as statisticians and social scientists, who have some knowledge of probability theory and regression analysis, will find this work a valuable introduction to logit and probit analysis -- techniques that can, and should, be used in many research situations.

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