GOODNESS-OF-FIT TESTS FOR ORDINAL RESPONSE REGRESSION-MODELS

In this paper, goodness-of-fit test statistics for ordinal regression models are proposed, which have approximate chi(2)-distributions when the model has been correctly specified. The statistics proposed can be viewed as extensions of the Hosmer-Lemeshow statistic to ordinal cate gorical data and can be easily calculated by using existing statistica l software for analysing ordinal response data The methods are illustr ated by using data from an arthritis clinical trial comparing the drug auranofin and placebo therapy for the treatment of rheumatoid arthrit is, in which the response is a self-assessment of arthritis, classifie d as poor, fair and good. The covariates of interest are age, gender, treatment and base-line response. A proportional odds model is fitted to the data, and the proposed goodness-of-fit statistics are applied t o the fitted model. Also, the small sample properties of the proposed goodness-of-fit statistics are compared in a simulation study.