JSM 2005 - Toronto

Abstract #303011

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 73
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #303011
Title: Incorporating Multiple Observations into Logistic Regression Models of Incident Disease
Author(s): Julia Bienias*+ and Phillip S. Kott and Todd L. Beck and Denis A. Evans
Companies: Rush University Medical Center and National Agricultural Statistics Service and Rush University Medical Center and Rush University Medical Center
Address: 444 W Fullerton Pkwy, Chicago, IL, 60614, United States
Keywords: Complex surveys ; Poisson sampling ; Finite-population inference ; Longitudinal
Abstract:

The delete-a-group jackknife variance estimator is a useful tool for measuring variances under complex sampling designs. The technique divides the first-phase sample into mutually exclusive variance groups of nearly equal size, deletes one group at a time to create a set of replicates, and makes weighting adjustments in each replicate analogous to those done for the sample as a whole. Variance estimation proceeds in the standard (unstratified) jackknife fashion. We apply this method to a complex multi-wave longitudinal study, the Chicago Health and Aging Project, which examines risk factors for chronic health problems of older adults, particularly Alzheimer's disease. Every three years, all surviving members of the cohort are interviewed about a variety of health-related topics, including cognitive and physical function measures. At each wave, a "disease-free" cohort is identified, from which a stratified Poisson sample is drawn for detailed clinical evaluation of incident disease at the next wave.

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Revised March 2005