%0 Journal Article
%A Craiu, R.V.
%A Duchesne, T.
%A Fortin, D.
%T Inference Methods for the Conditional Logistic Regression Model with Longitudinal Data
%B Biometrical Journal
%D 2008
%V 50
%P 97-109
%N 1
%Z 10.1002/bimj.200610379; timestamp=(2008.02.18)
%X 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 alternative
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. (© 2008 WILEY-VCH Verlag GmbH & Co.
KGaA, Weinheim)
%# brugerolles
%F CraiuDuchesneFortin2008
%3 BibTeX type = ARTICLE