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The University of Chicago
Department of Statistics
Master’s Seminar
Department of Statistics
The University of Chicago
Fitting Regression Models Under Case-control Sampling
Wednesday, July 26, 2006 at 9:30 AM
110 Eckhart Hall, 5734 S. University Avenue
Data arising from case-control sampling are the result of complex design involving stratification of the response. Some methods are developed to fit the regression models under
case-control sampling for longitudinal data or for secondary analysis. For some models such
as Logistic and Poisson models, valid point estimators and asymptotic variance of the oddsratio parameters are obtained by modifying the prospective logistic regression model to cater
for this sampling scheme. The profile likelihood technique for binary response and usual survey weight method with weights inversely proportional to the selection probability are also
presented. The modified prospective method and weight method are applied on the analysis
of a simulated data set and an actual data set.
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