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Bioinformatics Advance Access originally published online on April 26, 2007
Bioinformatics 2007 23(12):1519-1526; doi:10.1093/bioinformatics/btm140
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Two-stage designs applying methods differing in costs

Alexandra Goll * and Peter Bauer

Section of Medical Statistics, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria

*To whom correspondence should be addressed.


  Abstract

Motivation: Two-stage pilot and integrated designs are powerful tools for investigating large numbers of hypotheses. Asymptotically, optimal two-stage designs controlling the familywise error or false discovery rate are considered when costs and effect sizes per measurement differ between stages and total costs are constrained.

Results: Depending on the cost and effect size ratios between the measurements, it is generally more powerful to apply two-stage procedures using one measurement method at both stages. For the practically relevant case that the same method is applied at both stages but designing the second-stage measurements raises extra costs, two-stage designs are more powerful than the single-stage design even for large costs ratios. The power of the optimal pilot and integrated two-stage designs generally are similar, however, the integrated approach is less sensitive even to severe design misspecifications in the planning phase.

Availability: R-programs (R, 2005) to calculate asymptotically optimal designs are available on: http://statistics.msi.meduniwien.ac.at/index.php?page=ao2stage

Contact: alexandra.goll{at}meduniwien.ac.at

Associate Editor: Martin Bishop

Received on February 9, 2007; revised on March 23, 2007; accepted on April 5, 2007

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