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Comparison of methods for adaptive sample size adjustment.

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Comparison of methods for adaptive sample size adjustment. / Friede, Tim; Kieser, Meinhard A.
In: Statistics in Medicine, Vol. 20, No. 24, 30.12.2001, p. 3861-3873.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Friede, T & Kieser, MA 2001, 'Comparison of methods for adaptive sample size adjustment.', Statistics in Medicine, vol. 20, no. 24, pp. 3861-3873. https://doi.org/10.1002/sim.972

APA

Friede, T., & Kieser, M. A. (2001). Comparison of methods for adaptive sample size adjustment. Statistics in Medicine, 20(24), 3861-3873. https://doi.org/10.1002/sim.972

Vancouver

Friede T, Kieser MA. Comparison of methods for adaptive sample size adjustment. Statistics in Medicine. 2001 Dec 30;20(24):3861-3873. doi: 10.1002/sim.972

Author

Friede, Tim ; Kieser, Meinhard A. / Comparison of methods for adaptive sample size adjustment. In: Statistics in Medicine. 2001 ; Vol. 20, No. 24. pp. 3861-3873.

Bibtex

@article{6fc34359f4fc4fabac52be76fad58fad,
title = "Comparison of methods for adaptive sample size adjustment.",
abstract = "In fixed sample size designs, precise knowledge about the magnitude of the outcome variable's variance in the planning phase of a clinical trial is mandatory for an adequate sample size determination. Wittes and Brittain introduced the internal pilot study design that allows recalculation of the sample size during an ongoing trial using the estimated variance obtained from an interim analysis. However, this procedure requires the unblinding of the treatment code. Since unblinding of an ongoing trial should be avoided whenever possible, there should be some benefit of this design compared with blinded sample size recalculation procedures to justify the unveiling of the treatment code. In this paper, we compare several sample size recalculation procedures with and without unblinding. The simulation results indicate that the procedures behave similarly. In particular, breaking of the blind is not required for an efficient sample size adjustment. We also compare these pure sample size adaptation procedures with study designs which additionally allow for early stopping. Evaluation of the cumulative distribution function of the resulting sample sizes shows that the option for early stopping may lead to lower expectation but generally to a higher variability. The procedures are illustrated by an example of a trial in the treatment of depression.",
author = "Tim Friede and Kieser, {Meinhard A.}",
year = "2001",
month = dec,
day = "30",
doi = "10.1002/sim.972",
language = "English",
volume = "20",
pages = "3861--3873",
journal = "Statistics in Medicine",
issn = "1097-0258",
publisher = "John Wiley and Sons Ltd",
number = "24",

}

RIS

TY - JOUR

T1 - Comparison of methods for adaptive sample size adjustment.

AU - Friede, Tim

AU - Kieser, Meinhard A.

PY - 2001/12/30

Y1 - 2001/12/30

N2 - In fixed sample size designs, precise knowledge about the magnitude of the outcome variable's variance in the planning phase of a clinical trial is mandatory for an adequate sample size determination. Wittes and Brittain introduced the internal pilot study design that allows recalculation of the sample size during an ongoing trial using the estimated variance obtained from an interim analysis. However, this procedure requires the unblinding of the treatment code. Since unblinding of an ongoing trial should be avoided whenever possible, there should be some benefit of this design compared with blinded sample size recalculation procedures to justify the unveiling of the treatment code. In this paper, we compare several sample size recalculation procedures with and without unblinding. The simulation results indicate that the procedures behave similarly. In particular, breaking of the blind is not required for an efficient sample size adjustment. We also compare these pure sample size adaptation procedures with study designs which additionally allow for early stopping. Evaluation of the cumulative distribution function of the resulting sample sizes shows that the option for early stopping may lead to lower expectation but generally to a higher variability. The procedures are illustrated by an example of a trial in the treatment of depression.

AB - In fixed sample size designs, precise knowledge about the magnitude of the outcome variable's variance in the planning phase of a clinical trial is mandatory for an adequate sample size determination. Wittes and Brittain introduced the internal pilot study design that allows recalculation of the sample size during an ongoing trial using the estimated variance obtained from an interim analysis. However, this procedure requires the unblinding of the treatment code. Since unblinding of an ongoing trial should be avoided whenever possible, there should be some benefit of this design compared with blinded sample size recalculation procedures to justify the unveiling of the treatment code. In this paper, we compare several sample size recalculation procedures with and without unblinding. The simulation results indicate that the procedures behave similarly. In particular, breaking of the blind is not required for an efficient sample size adjustment. We also compare these pure sample size adaptation procedures with study designs which additionally allow for early stopping. Evaluation of the cumulative distribution function of the resulting sample sizes shows that the option for early stopping may lead to lower expectation but generally to a higher variability. The procedures are illustrated by an example of a trial in the treatment of depression.

U2 - 10.1002/sim.972

DO - 10.1002/sim.972

M3 - Journal article

VL - 20

SP - 3861

EP - 3873

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 1097-0258

IS - 24

ER -