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Simple procedures for blinded sample size adjustment that do not affect the type I error rate.

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Simple procedures for blinded sample size adjustment that do not affect the type I error rate. / Kieser, Meinhard; Friede, Tim.
In: Statistics in Medicine, Vol. 22, No. 23, 15.12.2003, p. 2571-2581.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Kieser, M & Friede, T 2003, 'Simple procedures for blinded sample size adjustment that do not affect the type I error rate.', Statistics in Medicine, vol. 22, no. 23, pp. 2571-2581. https://doi.org/10.1002/sim.1585

APA

Vancouver

Kieser M, Friede T. Simple procedures for blinded sample size adjustment that do not affect the type I error rate. Statistics in Medicine. 2003 Dec 15;22(23):2571-2581. doi: 10.1002/sim.1585

Author

Kieser, Meinhard; ; Friede, Tim. / Simple procedures for blinded sample size adjustment that do not affect the type I error rate. In: Statistics in Medicine. 2003 ; Vol. 22, No. 23. pp. 2571-2581.

Bibtex

@article{d1352a2916a94c2ea6674b94feafa578,
title = "Simple procedures for blinded sample size adjustment that do not affect the type I error rate.",
abstract = "For normally distributed data, determination of the appropriate sample size requires a knowledge of the variance. Because of the uncertainty in the planning phase, two-stage procedures are attractive where the variance is reestimated from a subsample and the sample size is adjusted if necessary. From a regulatory viewpoint, preserving blindness and maintaining the ability to calculate or control the type I error rate are essential. Recently, a number of proposals have been made for sample size adjustment procedures in the t-test situation. Unfortunately, none of these methods satisfy both these requirements. We show through analytical computations that the type I error rate of the t-test is not affected if simple blind variance estimators are used for sample size recalculation. Furthermore, the results for the expected power of the procedures demonstrate that the methods are effective in ensuring the desired power even under initial misspecification of the variance. A method is discussed that can be applied in a more general setting and that assumes analysis with a permutation test. This procedure maintains the significance level for any design situation and arbitrary blind sample size recalculation strategy.",
keywords = "clinical trial • internal pilot study • sample size adjustment • two-stage design",
author = "Meinhard; Kieser and Tim Friede",
year = "2003",
month = dec,
day = "15",
doi = "10.1002/sim.1585",
language = "English",
volume = "22",
pages = "2571--2581",
journal = "Statistics in Medicine",
issn = "1097-0258",
publisher = "John Wiley and Sons Ltd",
number = "23",

}

RIS

TY - JOUR

T1 - Simple procedures for blinded sample size adjustment that do not affect the type I error rate.

AU - Kieser, Meinhard;

AU - Friede, Tim

PY - 2003/12/15

Y1 - 2003/12/15

N2 - For normally distributed data, determination of the appropriate sample size requires a knowledge of the variance. Because of the uncertainty in the planning phase, two-stage procedures are attractive where the variance is reestimated from a subsample and the sample size is adjusted if necessary. From a regulatory viewpoint, preserving blindness and maintaining the ability to calculate or control the type I error rate are essential. Recently, a number of proposals have been made for sample size adjustment procedures in the t-test situation. Unfortunately, none of these methods satisfy both these requirements. We show through analytical computations that the type I error rate of the t-test is not affected if simple blind variance estimators are used for sample size recalculation. Furthermore, the results for the expected power of the procedures demonstrate that the methods are effective in ensuring the desired power even under initial misspecification of the variance. A method is discussed that can be applied in a more general setting and that assumes analysis with a permutation test. This procedure maintains the significance level for any design situation and arbitrary blind sample size recalculation strategy.

AB - For normally distributed data, determination of the appropriate sample size requires a knowledge of the variance. Because of the uncertainty in the planning phase, two-stage procedures are attractive where the variance is reestimated from a subsample and the sample size is adjusted if necessary. From a regulatory viewpoint, preserving blindness and maintaining the ability to calculate or control the type I error rate are essential. Recently, a number of proposals have been made for sample size adjustment procedures in the t-test situation. Unfortunately, none of these methods satisfy both these requirements. We show through analytical computations that the type I error rate of the t-test is not affected if simple blind variance estimators are used for sample size recalculation. Furthermore, the results for the expected power of the procedures demonstrate that the methods are effective in ensuring the desired power even under initial misspecification of the variance. A method is discussed that can be applied in a more general setting and that assumes analysis with a permutation test. This procedure maintains the significance level for any design situation and arbitrary blind sample size recalculation strategy.

KW - clinical trial • internal pilot study • sample size adjustment • two-stage design

U2 - 10.1002/sim.1585

DO - 10.1002/sim.1585

M3 - Journal article

VL - 22

SP - 2571

EP - 2581

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 1097-0258

IS - 23

ER -