Abstract #301460

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JSM 2003 Abstract #301460
Activity Number: 332
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #301460
Title: Goodness-of-fit Testing for Ordinal Models Fitted with Continuous Covariates
Author(s): Susan Moss*+ and Huiman X. Barnhart and John M. Williamson
Companies: Centers for Disease Control and Prevention and Emory University and Centers for Disease Control and Prevention
Address: 1820 New York Ave., Atlanta, GA, 30307,
Keywords: ordinal regression ; goodness of fit ; sparse data ; Pearson's chi square ; unweighted sum of squares
Abstract:

We develop two new goodness-of-fit test statistics based on "increasing cells" asymptotics for ordinal models fitted with continuous covariates. The proposed tests are standardized versions of Pearson's chi-square test and the unweighted sum of squares test and are asymptotically normal as the number of distinct covariate groups increases with increasing sample size. Simulations were conducted to evaluate the performance of the tests in finite samples sizes with various alternative models. Application of the tests is illustrated with data from a clinical trial comparing the drug auranofin and placebo therapy for the treatment of rheumatoid arthritis where the response is classified as poor, fair, or good, and covariates of interest include age, gender, treatment, and baseline response.

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