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Activity Number: 146
Type: Invited
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #303667
Title: Beyond the Case-Control Study
Author(s): Norman E. Breslow*+
Companies: University of Washington
Address: Departmenf of Biostatistics, Seattle, WA, 98155-7232,
Keywords: epidemiology ; survey sampling ; semiparametric efficiency ; R package ; missing data

In a standard epidemiologic study design, cases and controls are sampled from a defined finite population such as a health maintenance organization. Additional data, e.g. from biological assay of stored tissue, are collected for sampled subjects. Considerable existing information about the members of this finite population NOT sampled as cases or controls, however, is often ignored both in study design and in data analysis.

Various proposals have been made for recovery of this neglected information. One is to view the problem as a missing data problem and invoke methods of semi-parametric efficient inference. Another is to view the problem as a sample survey problem, adjusting the sampling weights to improve efficiency. The two approaches differ in the tradeoff between bias and efficiency, particularly when the model is misspecified.

This talk reviews some options available for incorporation of additional information in the design and analysis of case-control studies. Differences between them are explored via simulation of control samples using records from the National Wilms Tumor Study and analysis of the simulated data using the R survey and osDesign packages.

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