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024 7 _ |a 10.1080/10543406.2013.860158
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024 7 _ |a pmid:24605976
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024 7 _ |a 1054-3406
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024 7 _ |a 1520-5711
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037 _ _ |a DKFZ-2017-03849
041 _ _ |a eng
082 _ _ |a 570
100 1 _ |a Kunz, Christina
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245 _ _ |a Blinded versus unblinded covariate selection in confirmatory survival trials.
260 _ _ |a Philadelphia, PA
|c 2014
|b Taylor & Francis
336 7 _ |a article
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336 7 _ |a ARTICLE
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336 7 _ |a Journal Article
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520 _ _ |a 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.
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700 1 _ |a Kieser, Meinhard
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773 _ _ |a 10.1080/10543406.2013.860158
|g Vol. 24, no. 2, p. 398 - 414
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|t Journal of biopharmaceutical statistics
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909 C O |o oai:inrepo02.dkfz.de:127827
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910 1 _ |a Deutsches Krebsforschungszentrum
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