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000127827 0247_ $$2ISSN$$a1054-3406
000127827 0247_ $$2ISSN$$a1520-5711
000127827 037__ $$aDKFZ-2017-03849
000127827 041__ $$aeng
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000127827 1001_ $$0P:(DE-He78)a9f6104e5c2c26345dcb242e6bdcb2b2$$aKunz, Christina$$b0$$eFirst author$$udkfz
000127827 245__ $$aBlinded versus unblinded covariate selection in confirmatory survival trials.
000127827 260__ $$aPhiladelphia, PA$$bTaylor & Francis$$c2014
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000127827 520__ $$aAdjustment 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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000127827 7001_ $$aKieser, Meinhard$$b1
000127827 773__ $$0PERI:(DE-600)2008925-9$$a10.1080/10543406.2013.860158$$gVol. 24, no. 2, p. 398 - 414$$n2$$p398 - 414$$tJournal of biopharmaceutical statistics$$v24$$x1520-5711$$y2014
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