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Logit Modeling

Alfred DeMaris
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QASS
Quantitative Applications in the Social Sciences
Quantitative/Statistical Research
QuantitativeStatistical Research
Regression & Correlation
Research Methods in Psychology

Product details

  • ISBN 9780803943773
  • Weight: 140g
  • Dimensions: 139 x 215mm
  • Publication Date: 20 Jul 1992
  • Publisher: SAGE Publications Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Description

Logit Modeling represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, especially when the measurement assumptions for classical multiple regression fail to be met. Taking an applied approach, DeMaris begins by describing the logit model in the context of the general loglinear model, moving its application from two-way to multidimensional tables. He then divides the rest of the book between an examination of the varieties of logit models for contingency tables and logistic regression. Throughout his coverage of both these major areas, DeMaris emphasizes interpretation of results. The book concludes with an extension of logistic regression to dependent variables with more than two categories. Logit Modeling is the perfect answer for those seeking a comprehensive guide for the entire range of logit models.


represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, especially when the measurement assumptions for classical multiple regression fail to be met. Taking an applied approach, DeMaris begins by describing the logit model in the context of the general loglinear model, moving its application from two-way to multidimensional tables. He then divides the rest of the book between an examination of the varieties of logit models for contingency tables and logistic regression. Throughout his coverage of both these major areas, DeMaris emphasizes interpretation of results. The book concludes with an extension of logistic regression to dependent variables with more than two categories. is the perfect answer for those seeking a comprehensive guide for the entire range of logit models.
About Alfred DeMaris
Alfred DeMaris is Professor of Sociology and Statistician for the Center for Family and Demographic Research at Bowling Green State University in Bowling Green, Ohio. His substantive interests are focused on romantic relationships, including issues surrounding premarital cohabitation, the prediction of marital instability, and the antecedents and consequences of violence in heterosexual dyads. His work in these areas has appeared in Social Forces, Social Psychology Quarterly, Journal of Marriage and Family, Journal of Family Issues, Family Relations, and Journal of Sex Research. His primary specialty in social statistics is regression modeling, in particular, logistic regression. His articles on this topic have appeared in Social Forces, Psychological Bulletin, and Sociological Methods & Research, among other venues. He is also the author of Logit Modeling: Practical Applications (1992, Sage) and Regression with Social Data: Modeling Continuous and Limited Response Variables (2004, Wiley).

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