This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 618
Type: Topic Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Health Policy Statistics Section
Abstract - #309329
Title: Coherent Analysis of Longitudinal Changes in Biomarkers in the Presence of Attrition Due to Competing Risks
Author(s): Tom Greene*+
Companies: The University of Utah
Address: , , ,
Keywords: principal stratification ; biomarker ; truncation-by-death ; causal inference ; pattern mixture model
Abstract:

We consider the problem of estimating effects of treatments and exposures on longitudinal biomarkers for cohorts with high rates of attrition due to death or other competing risks. In this situation intended biomarker measurements occurring after competing events are undefined, so that standard methods for longitudinal analysis with missing data do not apply. Recently this type of problem has been addressed by applying the causal modeling framework of principal stratification to estimate effects on the biomarker for those patients who would survive without competing risks irrespective of the treatment or exposure level. We present a new approach to this problem that uses a pattern mixture model to relate the longitudinal biomarker to the event times for the competing risk in conjunction with a local rank preserving structural model to identify the appropriate subgroup for analysis.


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