The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
... MATHIOWETZ, and SUDMAN - Measurement Errors in Surveys COCHRAN - Sampling Techniques, Third Edition COUPER, BAKER, BETHLEHEM, CLARK, MARTIN, NICHOLLS, and O'REILLY (editors) - Computer Assisted Survey Information Collection COX, ...
Other methods for exploring additive interaction have been considered in the literature including most popularly the Relative Excess Risk due to Interaction or RERI [Rothman et al. (2008); Hosmer and Lemeshow (1992)].
In this text, author Scott Menard provides coverage of not only the basic logistic regression model but also advanced topics found in no other logistic regression text.
From the reviews of the First Edition.
'Tis better to use a logit or probit link function than to inappropriately use ordinary least squares regression with binary or categorical dependent variables . . .” —attributed to Warren Shakespeare, William's younger statistician ...
From the reviews of the First Edition.
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from ...
... Indicators Sullivan/Feldman Exploratory Data Analysis Hartwig/Dearing Reliability and Validity Assessment Carmines/Zeller Analyzing Panel Data Markus Discriminant Analysis Klecka Log-Linear Models Knoke/Burke Interrupted Time Series ...
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Rothman,K.J. and Greenland,S. (1998). Modern Epidemiology.3rd edition. LippincottRaven., Philadelphia, PA. Royston, P(2001). Flexible parametric alternatives to the Coxmodeland more. TheStata Journal, 1(1 ): 1–28. Royston, P.(2004).