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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Two-stage designs applying methods differing in costs
Section of Medical Statistics, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria
*To whom correspondence should be addressed.
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Abstract |
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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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