JSM 2004 - Toronto

Abstract #301645

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Activity Number: 437
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #301645
Title: Bias-corrected Spearman Rank Correlation Coefficient
Author(s): William W.B. Wang*+ and Li Huiling and Ivan S.F. Chan
Companies: Merck & Co., Inc. and Columbia University and Merck & Co., Inc.
Address: 785 Jolly Rd., Blue Bell, PA, 19422,
Keywords: Spearman's Rank Correlation ; Pearson Correlation ; bias correction ; confidence interval coverage ; vaccine clinical trial
Abstract:

Spearman rank correlation coefficient is a nonparametric statistic to measure the strength of association between two random variables, such as those for the cellular and humoral immune responses often measured in vaccine clinical trials. Even though Spearman correlation has been commonly used as a robust alternative to Pearson correlation, its statistical properties are neither popularly known nor well understood. We investigate the bias of Spearman rank correlation coefficient as an estimator of the population correlation coefficient. We point out that substantial bias may exist in some typical clinical data situations (and even with large sample size), resulting in poor coverage of the associated confidence interval. We propose a method to obtain the bias-corrected Spearman correlation and the associated confidence interval. Our simulation results show that this new method can dramatically reduce the bias and yield a confidence interval with proper coverage.

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