Sage university papers series. Quantitative applications in the social sciences ;
no. 07-045
Includes bibliographical references (pages 93-94).
The linear probability model -- Specification of nonlinear probability models -- Estimation of probit and logit models for dichotomous dependent variables -- Minimum chi-square estimation and polytomous models -- Minimum chi-square estimation and polytomous models -- Summary and extensions.
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After showing why ordinary regression analysis is not appropriate for investigating dichotomous or otherwise 'limited' dependent variables, this volume examines three techniques which are well suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models.
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