Linear probability, logit, and probit models:
Gespeichert in:
Bibliographische Detailangaben
Beteilige Person: Aldrich, John H. (VerfasserIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Beverly Hills Sage Publications c1984
Schriftenreihe:Quantitative applications in the social sciences no. 07-045
Schlagwörter:
Links:http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=24734
Beschreibung:Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002
Includes bibliographical references (p. 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
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
Umfang:1 Online-Ressource (95 p.)
ISBN:0585216932
9780585216935
9781412984744
1412984742