Introduction In this chapter, the standard logistic model is extended to
handle outcome variables that have more than two ordered
categories. When the categories of the outcome variable
have a natural order, ordinal logistic regression may be
appropriate.
The mathematical form of one type of ordinal logistic
regression model, the proportional odds model, and its
interpretation are developed. The formulas for the odds
ratio and confidence intervals are derived, and techniques
for testing hypotheses and assessing the statistical signifi-
cance of independent variables are shown.Abbreviated
Outline
The outline below gives the user a preview of the material
to be covered by the presentation. A detailed outline for
review purposes follows the presentation.I. Overview (page 466)
II. Ordinal logistic regression: The proportional odds
model (pages 466–472)
III. Odds ratios and confidence limits (pages 472–475)
IV. Extending the ordinal model (pages 476–478)
V. Likelihood function for ordinal model (pages
478–479)
VI. Ordinal vs. multiple standard logistic regressions
(pages 479–481)
VII. Summary (page 481)464 13. Ordinal Logistic Regression