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Activity Number: 167
Type: Contributed
Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #313522 View Presentation
Title: Sample Size Reestimation for Ordinal Data Based on Conditional Power
Author(s): Emelita de Leon-Wong*+ and Liwei Wang
Companies: PPDI and PPDI
Keywords: conditional power ; sample size reestimation ; ordinal data
Abstract:

A sample size is planned to detect a clinically important difference in two independent samples with type I error and unconditional power. With uncertainties in the assumed difference or variance, sample size reestimation is performed. A common metrics for sample size reestimation is conditional power (CP). This paper assesses the performance of CP under the current data trend using B-value statistics for adaptively increasing sample size in comparing the distributions of stratified ordinal data in two independent samples with the generalized Cochran-Mantel-Haenszel (CMH). While known results like the square root of the CMH is normally distributed, B-value is normally distributed for normally distributed data, and the variance of the generalized CMH is approximately proportional to the planned total sample size indicate that CP based on the generalized CMH test may provide appropriate increases in sample size, it is not known how CP compares with other metrics like predictive power or posterior probability of success of determining the difference in the 2 samples with ordinal data. Simulated data with treatment by strata interaction will be used to assess CP performance.


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