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.