TY - JOUR
T1 - Flexible design for following up positive findings
AU - Yu, Kai
AU - Chatterjee, Nilanjan
AU - Wheeler, William
AU - Li, Qizhai
AU - Wang, Sophia
AU - Rothman, Nathaniel
AU - Wacholder, Sholom
N1 - Funding Information:
We thank Michael Proschan, Stephen Chanock, Mitchell Gail, Patricia Hartge, Gang Zheng, and two anonymous reviewers for valuable comments. This research was supported by the Intramural Program of the National Institutes of Health.
PY - 2007/9
Y1 - 2007/9
N2 - As more population-based studies suggest associations between genetic variants and disease risk, there is a need to improve the design of follow-up studies (stage II) in independent samples to confirm evidence of association observed at the initial stage (stage I). We propose to use flexible designs developed for randomized clinical trials in the calculation of sample size for follow-up studies. We apply a bootstrap procedure to correct the effect of regression to the mean, also called "winner's curse," resulting from choosing to follow up the markers with the strongest associations. We show how the results from stage I can improve sample size calculations for stage II adaptively. Despite the adaptive use of stage I data, the proposed method maintains the nominal global type I error for final analyses on the basis of either pure replication with the stage II data only or a joint analysis using information from both stages. Simulation studies show that sample-size calculations accounting for the impact of regression to the mean with the bootstrap procedure are more appropriate than is the conventional method. We also find that, in the context of flexible design, the joint analysis is generally more powerful than the replication analysis.
AB - As more population-based studies suggest associations between genetic variants and disease risk, there is a need to improve the design of follow-up studies (stage II) in independent samples to confirm evidence of association observed at the initial stage (stage I). We propose to use flexible designs developed for randomized clinical trials in the calculation of sample size for follow-up studies. We apply a bootstrap procedure to correct the effect of regression to the mean, also called "winner's curse," resulting from choosing to follow up the markers with the strongest associations. We show how the results from stage I can improve sample size calculations for stage II adaptively. Despite the adaptive use of stage I data, the proposed method maintains the nominal global type I error for final analyses on the basis of either pure replication with the stage II data only or a joint analysis using information from both stages. Simulation studies show that sample-size calculations accounting for the impact of regression to the mean with the bootstrap procedure are more appropriate than is the conventional method. We also find that, in the context of flexible design, the joint analysis is generally more powerful than the replication analysis.
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U2 - 10.1086/520678
DO - 10.1086/520678
M3 - Article
C2 - 17701899
AN - SCOPUS:34548219537
VL - 81
SP - 540
EP - 551
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
SN - 0002-9297
IS - 3
ER -