|
Title
|
|
JASA, Theory and Methods Invited Session
|
|
Date / Time / Room
|
Sponsor
|
Type
|
08/12/2002
10:30 AM -
12:20 PM
Room: S-New York Ballroom A
|
JASA, Theory and Methods
|
Invited
|
|
Organizer:
|
Martin A. Tanner, Northwestern University
|
|
Chair:
|
Martin A. Tanner, Northwestern University
|
|
Discussant:
|
11:20 AM - Robert Elston, Case Western Reserve University
11:35 AM - Daniel J. Schaid, Mayo Clinic
11:50 AM - Norman Kaplan, National Institute of Environmental Health Sciences
|
|
Floor Discussion
|
12:05 PM
|
Description
Population heterogeneity is a potential source of confounding in genetic epidemiology. Unlike observational studies generally, in genetic epidemiology, exact methods may be derived for adjusting for confounding due to heterogeneity. These exact methods are founded on the randomness inherent in the transmission of genetic material from parents to children, and, in the simplest cases, involve conditioning on parental genotypes. This conditioning strategy is not available, of course, when parental genotypes are missing or incomplete. However, a basis for extending the strategy to incomplete data lies in noting that parental genotypes are complete minimal sufficient statistics for the nuisance parameters; in many cases, non-trivial minimal sufficient statistics can be computed and conditioned on to avoid confounding. Unfortunately, in many situations with missing or incomplete data, the minimal sufficient statistics are not complete, and conditioning strategies may fail to exploit available information. In such cases, score statistics that make use of all of the available information may be derived
as the result of regression calculations.
|
|
