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Sample-size calculations for studies with correlated ordinal outcomes
Authors:Kim Hae-Young  Williamson John M  Lyles Cynthia M
Institution:Division of HIV/AIDS Prevention (MS E-37), National Centers for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, 1600 Clifton Rd., NE, Atlanta, GA 30333, USA. kimhy@email.unc.edu
Abstract:Correlated ordinal response data often arise in public health studies. Sample-size (power) calculations are a crucial step in designing such studies to ensure an adequate sample to detect a significant effect. Here we extend Rochon's method of sample-size estimation with a repeated binary response to the ordinal case. The proposed sample-size calculations are based on an analysis with generalized estimating equations (GEE) and inference with the Wald test. Simulation results demonstrate the merit of the proposed power calculations. Analysis of an arthritis clinical trial is used for illustration.
Keywords:correlated data  generalized estimating equations  ordinal response  power  sample size
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