Logistic Regression Models for Ordinal Response Variables (Quantitative Applications in the Social Sciences)

Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of the cumulative (proportional) odds, continuation ratio, and adjacent category models for ordinal data. Description and examples of partial proportional odds models are also provided. This book is highly readable, with lots of examples and in-depth explanations and interpretations of model characteristics. SPSS and SAS are used for all examples; data and syntax are available from the author′s website. The examples are drawn from an educational context, but applications to other fields of inquiry are noted, such as HIV prevention, behavior change, counseling psychology, social psychology, etc.).  The level of the book is set for applied researchers who need to quickly understand the use and application of these kinds of ordinal regression models.

Scholarly Interests Statistical methods, with an emphasis on single and multilevel generalized linear models; evaluation of professional development and health/education programs or interventions, particularly for HIV prevention; secondary analysis of large-scale databases; capacity building for community-based organizations; translation of evidence-based interventions.