Modeling sensitivity and specificity with a time-varying reference standard within a longitudinal setting

Qin Yu, Wan Tang, Sue Marcus, Yan Ma, Hui Zhang and Xin Tu

Journal of Applied Statistics, 2010, vol. 37, issue 7, 1213-1230

Abstract: Diagnostic tests are used in a wide range of behavioral, medical, psychosocial, and healthcare-related research. Test sensitivity and specificity are the most popular measures of accuracy for diagnostic tests. Available methods for analyzing longitudinal study designs assume fixed gold or reference standards and as such do not apply to studies with dynamically changing reference standards, which are especially popular in psychosocial research. In this article, we develop a novel approach to address missing data and other related issues for modeling sensitivity and specificity within such a time-varying reference standard setting. The approach is illustrated with real as well as simulated data.

Keywords: augmented inverse probability weighted (AIPW) estimate; bivariate monotone missing data pattern (BMMDP); diagnostic test; double robust estimate; inverse probability weighted (IPW) estimate; missing data (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1080/02664760902998444

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