- We will send in 10–14 business days.
/images/books/4354102/9780803943773.jpg)
- Author: Alfred DeMaris
- Publisher: SAGE Publications, Inc
- ISBN-10: 0803943776
- ISBN-13: 9780803943773
- Format: 13.9 x 22.1 x 0.6 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Reviews
Description
Logit Modeling represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, particularly whenever 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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 14d.06:02:40
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Alfred DeMaris
- Publisher: SAGE Publications, Inc
- ISBN-10: 0803943776
- ISBN-13: 9780803943773
- Format: 13.9 x 22.1 x 0.6 cm, softcover
- Language: English English
Logit Modeling represents a breakthrough for researchers because it offers ways for more efficient estimation of models with multiple categorical variables, particularly whenever 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.
Reviews