Ordinal Regression

by G. David Garson

An illustrated tutorial and introduction to ordinal regression analysis using SPSS, SAS, or Stata. Suitable for introductory graduate-level study.The 2014 edition is a major update to the 2012 edition. Among the new features are Over double the page length (93 pp. rather than 46)* Fifty percent more figures (52 illustrations)* Now covers SAS and Stata as well as SPSS* Now covers partial proportional odds models(recommended when the parallel lines test fails in ordinary ordinal regression, which it frequently does)* Totally rewritten and reformatted, with new FAQs added* Links to download datasets used in the text.-Below is the unformatted table of contents.ORDINAL REGRESSIONOverview7Data examples in this volume8Key Terms and Concepts9Location variables and thresholds9Prediction equations9Ordinal Regression in SPSS9Overview9SPSS inputs10The main "Ordinal Regression" dialog10The Ordinal Regression "Location" dialog14The Ordinal Regression "Options" dialog17The Ordinal Regression "Scale" dialog19The Ordinal Regression "Bootstrap" dialog20The Ordinal Regression "Output" dialog22SPSS outputs23Overview23The parallel lines test24Tests and effect size measures for model goodness of fit25Parameter estimates28Odds ratios31Other output35Ordinal Regression in SAS39Overview39SAS syntax for ordinal regression39SAS output for ordinal regression41The parallel lines test41Testing the global null hypothesis42Parameter estimates42Type 3 Analysis of Effects43Odds ratio estimates44R-square44Association of predicted probabilities and observed responses45Model fit statistics45Saving estimates46Ordinal regression in Stata46Overview46Stata input for ordinal regression47Stata output for ordinal regression47The parallel lines test47Overview49Likelihood ratio test of the model50Pseudo-R250Parameter estimates51Odds ratios51Model fit statistics52Saving estimates53Other Stata statistical output53Partial proportional odds models54Overview54Partial proportional odds models in SAS55Partial proportional odds models in SAS56Example56Overview56Determining variables to constrain56The PPO model60Interpreting PPO results61Likelihood ratio tests63Partial proportional odds models in Stata65Example65Overview65Categorical predictor variables66Determining variables to constrain66The PPO model69Interpreting PPO results69Likelihood ratio tests72Postestimation74Assumptions74Parallel lines assumption74Adequate cell count76One ordinal dependent variable78Data level of predictor variables79Normal distribution of the dependent variable79Adequate sample size79No complete or quasi-complete separation79Absence of high multicollinearity80Frequently Asked Questions80Why not use ordinary least-squares regression instead of ordinal (logit) regression?80Why not use ANOVA instead of ordinal (logit) regression?80Why do parameter estimates differ between packages, and what is "parameterization"?81Does the direction of coding of the ordinal dependent matter?81How do I save predicte

99 pages, Kindle Edition

First published June 11, 2013