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Understanding the Proportional Odds Assumption in Clinical Trials

Statistical Consultancy Team

Ordinal scales are commonly used to assess clinical outcomes; however, the choice of analysis is often sub-optimal.  In 2007, the Optimising Analysis of Stroke Trials (OAST) collaboration showed that ordinal-appropriate analyses of ordinal stroke outcome scales were preferable over binary analysis of a chosen ‘favourable’ outcome[1] but uptake of ordinal methods between 2007 and 2014 has been low [2].

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Topics: Randomization, SAS Programming, Biostatistics Consulting, Statistics, Ordinal Logistic Regression, Proportional Odds Assumption, PROC Logistic, Neurology

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