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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 wellsuited for such data. It reviews the linear probability model and discusses alternative specifications of nonlinear models. Using detailed examples, Aldrich and Nelson point out the differences among linear, logit, and probit models, and explain the assumptions associated with each.
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This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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