On inference for Kendall's τ within a longitudinal data setting

Yan Ma

Journal of Applied Statistics, 2012, vol. 39, issue 11, 2441-2452

Abstract: Kendall's τ is a non-parametric measure of correlation based on ranks and is used in a wide range of research disciplines. Although methods are available for making inference about Kendall's τ, none has been extended to modeling multiple Kendall's τs arising in longitudinal data analysis. Compounding this problem is the pervasive issue of missing data in such study designs. In this article, we develop a novel approach to provide inference about Kendall's τ within a longitudinal study setting under both complete and missing data. The proposed approach is illustrated with simulated data and applied to an HIV prevention study.

Date: 2012
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DOI: 10.1080/02664763.2012.712954

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