Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences)
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Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences)
- Used Book in Good Condition
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.
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