Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - A bootstrap procedure for adaptive selection of the test statistic in flexible two-stage designs.
AU - Keiser, Meinhard
AU - Schneider, Brit
AU - Friede, Tim
PY - 2002
Y1 - 2002
N2 - Adaptive two-stage designs allow a data-driven change of design characteristics during the ongoing trial. One of the available options is an adaptive choice of the test statistic for the second stage of the trial based on the results of the interim analysis. Since there is often only a vague knowledge of the distribution shape of the primary endpoint in the planning phase of a study, a change of the test statistic may then be considered if the data indicate that the assumptions underlying the initial choice of the test are not correct. Collings and Hamilton proposed a bootstrap method for the estimation of the power of the two-sample Wilcoxon test for shift alternatives. We use this approach for the selection of the test statistic. By means of a simulation study, we show that the gain in terms of power may be considerable when the initial assumption about the underlying distribution was wrong, whereas the loss is relatively small when in the first instance the optimal test statistic was chosen. The results also hold true for comparison with a one-stage design. Application of the method is illustrated by a clinical trial example.
AB - Adaptive two-stage designs allow a data-driven change of design characteristics during the ongoing trial. One of the available options is an adaptive choice of the test statistic for the second stage of the trial based on the results of the interim analysis. Since there is often only a vague knowledge of the distribution shape of the primary endpoint in the planning phase of a study, a change of the test statistic may then be considered if the data indicate that the assumptions underlying the initial choice of the test are not correct. Collings and Hamilton proposed a bootstrap method for the estimation of the power of the two-sample Wilcoxon test for shift alternatives. We use this approach for the selection of the test statistic. By means of a simulation study, we show that the gain in terms of power may be considerable when the initial assumption about the underlying distribution was wrong, whereas the loss is relatively small when in the first instance the optimal test statistic was chosen. The results also hold true for comparison with a one-stage design. Application of the method is illustrated by a clinical trial example.
KW - Flexible two-stage designs • Bootstrap procedure • Power estimation • Sample size calculation
U2 - 10.1002/1521-4036(200207)44:5<641::AID-BIMJ641>3.0.CO;2-X
DO - 10.1002/1521-4036(200207)44:5<641::AID-BIMJ641>3.0.CO;2-X
M3 - Journal article
VL - 44
SP - 641
EP - 652
JO - Biometrical Journal
JF - Biometrical Journal
SN - 1521-4036
IS - 5
ER -