Inference for the median residual life function in sequential multiple assignment randomized trials. (20th November 2013)

• Record Type: Journal Article
• Authors: Kidwell, Kelley M.; Ko, Jin H.; Wahed, Abdus S.
• Is Part Of: Statistics in medicine. Volume 33:Number 9(2014)
• Page Start: 1503
• Page End: 1513
• Publication Date: 2013-11-20
• Subjects: Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.6042
• Languages: English
• ISSNs: 0277-6715

Abstract

<abstract abstract-type="main" id="sim6042-abs-0001"> <title>Abstract</title> <p id="sim6042-para-0001">In survival analysis, median residual lifetime is often used as a summary measure to assess treatment effectiveness; it is not clear, however, how such a quantity could be estimated for a given dynamic treatment regimen using data from sequential randomized clinical trials. We propose a method to estimate a dynamic treatment regimen‐specific median residual life (MERL) function from sequential multiple assignment randomized trials. We present the MERL estimator, which is based on inverse probability weighting, as well as, two variance estimates for the MERL estimator. One variance estimate follows from Lunceford, Davidian and Tsiatis' 2002 survival function‐based variance estimate and the other uses the sandwich estimator. The MERL estimator is evaluated, and its two variance estimates are compared through simulation studies, showing that the estimator and both variance estimates produce approximately unbiased results in large samples. To demonstrate our methods, the estimator has been applied to data from a sequentially randomized leukemia clinical trial. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>