Title of article :
Modeling sensitivity and specificity with a time-varying reference standard within a longitudinal setting
Author/Authors :
Qin Yu، نويسنده , , Wan Tang، نويسنده , , Sue Marcus، نويسنده , , Yan Ma، نويسنده , , Hui Zhang & Xin Tu، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
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 :
double robust estimate , inverse probability weighted (IPW) estimate , augmented inverse probability weighted (AIPW) estimate , diagnostic test , bivariate monotone missing datapattern (BMMDP) , Missing data
Journal title :
JOURNAL OF APPLIED STATISTICS
Journal title :
JOURNAL OF APPLIED STATISTICS