Testing Equality in Ordinal Data with Repeated Measurements: A Model-Free Approach

Lui Kung-Jong ()
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Lui Kung-Jong: San Diego State University

The International Journal of Biostatistics, 2016, vol. 12, issue 2, 10

Abstract: In randomized clinical trials, we often encounter ordinal categorical responses with repeated measurements. We propose a model-free approach with using the generalized odds ratio (GOR) to measure the relative treatment effect. We develop procedures for testing equality of treatment effects and derive interval estimators for the GOR. We further develop a simple procedure for testing the treatment-by-period interaction. To illustrate the use of test procedures and interval estimators developed here, we consider two real-life data sets, one studying the gender effect on pain scores on an ordinal scale after hip joint resurfacing surgeries, and the other investigating the effect of an active hypnotic drug in insomnia patients on ordinal categories of time to falling asleep.

Keywords: testing equality; interval estimators; generalized odds ratio; ordinal data; repeated measurements; model-free (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1515/ijb-2015-0075

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