期刊
BIOMETRICAL JOURNAL
卷 50, 期 1, 页码 97-109出版社
WILEY
DOI: 10.1002/bimj.200610379
关键词
akaike information criterion (AIC); case-control logistic regression; estimating equations; generalized estimating equations; Quasi-likelihood under independence criterion (QIC); retrospective sampling; Robust sandwich estimators
This paper considers inference methods for case-control logistic regression in longitudinal setups. The motivation is provided by an analysis of plains bison spatial location as a function of habitat heterogeneity. The sampling is done according to a longitudinal matched case-control design in which, at certain time points, exactly one case, the actual location of an animal, is matched to a number of controls, the altenative locations that could have been reached. We develop inference methods for the conditional logistic regression model in this setup, which can be formulated within a generalized estimating equation (GEE) framework. This permits the use of statistical techniques developed for GEE-based inference, such as robust variance estimators and model selection criteria adapted for non-independent data. The performance of the methods is investigated in a simulation study and illustrated with the bison data analysis.
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