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Bioinformatics Advance Access published online on April 26, 2007
Bioinformatics, 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. Peter Bauer, E-mail: Peter.Bauer{at}meduniwien.ac.at


  Abstract

Motivation: Two-stage pilot and integrated designs are powerful tools for investigating large numbers of hypotheses. Asymptotically optimal two-stage designs controlling the family wise 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 singlestage 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 to calculate asymptotically optimal designsare available on: http://statistics.msi.meduniwien.ac.at/index.php?page=ao2stage

Associate Editor: Prof. Martin Bishop

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

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