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Partial Proportional Odds Models for Ordinal Response Variables

Bercedis Peterson and Frank E. Harrell, Jr
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 39, No. 2 (1990), pp. 205-217
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2347760
Stable URL: http://www.jstor.org/stable/2347760
Page Count: 13
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Partial Proportional Odds Models for Ordinal Response Variables
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Abstract

The ordinal logistic regression model that McCullagh calls the proportional odds model is extended to models that allow non-proportional odds for a subset of the explanatory variables. The maximum likelihood method is used for estimation of parameters of general and restricted partial proportional odds models as well as for the derivation of Wald, Rao score and likelihood ratio tests. These tests assess association without assuming proportional odds and test proportional odds against various alternatives. Simulation results compare the score test for proportional odds with tests suggested by Koch, Amara and Singer that are based on a series of binary logistic models.

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