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Activity Number:
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531
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract #320146
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View Presentation
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Title:
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Adjusting for Dependent Truncation with Inverse Probability Weighting
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Author(s):
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Jing Qian* and Rebecca Betensky
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Companies:
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University of Massachusetts - Amherst and Harvard
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Keywords:
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censoring ;
inverse probability weighting ;
qusi-independence ;
truncation
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Abstract:
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Many clinical trials and observational studies are conducted under complex sampling involving truncation. Ignoring the issue of truncation or incorrectly assuming quasi-independence can lead to bias and incorrect results. Currently available approaches for dependently truncated data are sparse. We present an inverse probability weighting method for estimating the survival function of a failure time subject to left truncation and right censoring. The proposed method allows adjusting for informative truncation due to variables affecting both event time and truncation time. We develop inverse probability of truncation weighted product-limit estimator and Cox partial likelihood estimator. Simulation studies show that the proposed method performs well in finite sample. We apply the proposed method to an Alzheimer's disease study.
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Authors who are presenting talks have a * after their name.
