This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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451
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #306956 |
Title:
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Optimal G-Estimation Mediation Analyses Under Departure from Sequential Ignorability
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Author(s):
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Rongmei Zhang*+ and Marshall M. Joffe and Thomas R. Ten Have
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Companies:
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University of Pennsylvania and University of Pennsylvania and University of Pennsylvania School of Medicine
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Address:
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503 Blockley Hall, Philadelphia, PA, 19104,
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Keywords:
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causal inference ;
structural nested model ;
randomized trials ;
post-randomization ;
weighting
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Abstract:
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We address several questions relating to the use of standard and causal approaches to estimating the joint and mediation effects of randomized treatments and a post-randomization variable. Unlike standard analyses, our approach does not assume that the post-randomization variable is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). G-estimation is used to obtain consistent estimators for parameters in a structural nested distribution model in which we allow interaction between the randomized intervention and the post-randomization factor. We show how to obtain the efficient estimators. We conduct simulations to compare the performance between standard and causal approaches, and between our optimal approach and simpler g-estimators. We apply our approach to a randomized cognitive therapy trial.
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