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Activity Number:
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518
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #304763 |
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Title:
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Causal Inference in Nested Case-Control Studies
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Author(s):
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Sherri Rose*+ and Mark J. van der Laan
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Companies:
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University of California, Berkeley and University of California, Berkeley
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Address:
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Division of Biostatistics, Berkeley, CA, 94720,
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Keywords:
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nested case-control study designs ; biased sampling designs ; causal inference ; causal effect ; variable importance measures ; targeted maximum likelihood estimation
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Abstract:
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A nested case-control study is conducted within a well-defined cohort arising out of a population of interest; however, the case control sample within the cohort is a biased sample. Methods for analyzing case-control studies have largely focused on logistic regression models that provide conditional and not marginal causal estimates of the odds ratio. We previously developed a Targeted Maximum Likelihood Estimation (TMLE) procedure for case-control study designs, which uses the prevalence probability in simple case-control weighting. We propose the use of our Case-Control Weighted TMLE procedure in nested case-control samples, where the prevalence probability is known or estimated from the cohort. For statistical inference, we view the nested case-control sample as a missing data problem (Robins et al., 1994).
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