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@ARTICLE{Kunz:127827,
author = {C. Kunz$^*$ and M. Kieser},
title = {{B}linded versus unblinded covariate selection in
confirmatory survival trials.},
journal = {Journal of biopharmaceutical statistics},
volume = {24},
number = {2},
issn = {1520-5711},
address = {Philadelphia, PA},
publisher = {Taylor $\&$ Francis},
reportid = {DKFZ-2017-03849},
pages = {398 - 414},
year = {2014},
abstract = {Adjustment for covariates and specification of the correct
covariate set are important issues in the analysis of
clinical trials. Edwards (1999) proposes a model selection
approach where the model is chosen on the final data set,
which remains blinded for treatment group allocation. We
investigate this method for time-to-event endpoints and
compare its performance to variable selection within an
adaptive design. This adaptive design integrates the methods
of Schäfer and Müller (2001) and Keiding et al. (1987) and
allows variable selection on the unblinded data during an
interim analysis. Monte Carlo simulation shows that Edwards'
method-though blinded-outperforms the adaptive method in
terms of ability to select the survival relevant covariates
and power. The application of the methods is illustrated by
a clinical trial example.},
cin = {C060},
ddc = {570},
cid = {I:(DE-He78)C060-20160331},
pnm = {313 - Cancer risk factors and prevention (POF3-313)},
pid = {G:(DE-HGF)POF3-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:24605976},
doi = {10.1080/10543406.2013.860158},
url = {https://inrepo02.dkfz.de/record/127827},
}