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A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection. / Magirr, Dominic; Jaki, Thomas; Whitehead, John.
In: Biometrika, Vol. 99, No. 2, 06.2012, p. 494-501.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Magirr, D, Jaki, T & Whitehead, J 2012, 'A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection', Biometrika, vol. 99, no. 2, pp. 494-501. https://doi.org/10.1093/biomet/ass002

APA

Magirr, D., Jaki, T., & Whitehead, J. (2012). A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection. Biometrika, 99(2), 494-501. https://doi.org/10.1093/biomet/ass002

Vancouver

Magirr D, Jaki T, Whitehead J. A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection. Biometrika. 2012 Jun;99(2):494-501. doi: 10.1093/biomet/ass002

Author

Magirr, Dominic ; Jaki, Thomas ; Whitehead, John. / A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection. In: Biometrika. 2012 ; Vol. 99, No. 2. pp. 494-501.

Bibtex

@article{20bda9fdd9f14cb2927996941424ff78,
title = "A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection",
abstract = "We generalize the Dunnett test to derive efficacy and futility boundaries for a flexible multi-arm multi-stage clinical trial for a normally distributed endpoint with known variance. We show that the boundaries control the familywise error rate in the strong sense. The method is applicable for any number of treatment arms, number of stages and number of patients per treatment per stage. It can be used for a wide variety of boundary types or rules derived from α-spending functions. Additionally, we show how sample size can be computed under a least favourable configuration power requirement and derive formulae for expected sample sizes.",
keywords = "Clinical trial , Dunnett test, Familywise error rate , Treatment selection",
author = "Dominic Magirr and Thomas Jaki and John Whitehead",
year = "2012",
month = jun,
doi = "10.1093/biomet/ass002",
language = "English",
volume = "99",
pages = "494--501",
journal = "Biometrika",
issn = "0006-3444",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - A generalized Dunnett Test for Multi-arm Multi-stage Clinical Studies with Treatment Selection

AU - Magirr, Dominic

AU - Jaki, Thomas

AU - Whitehead, John

PY - 2012/6

Y1 - 2012/6

N2 - We generalize the Dunnett test to derive efficacy and futility boundaries for a flexible multi-arm multi-stage clinical trial for a normally distributed endpoint with known variance. We show that the boundaries control the familywise error rate in the strong sense. The method is applicable for any number of treatment arms, number of stages and number of patients per treatment per stage. It can be used for a wide variety of boundary types or rules derived from α-spending functions. Additionally, we show how sample size can be computed under a least favourable configuration power requirement and derive formulae for expected sample sizes.

AB - We generalize the Dunnett test to derive efficacy and futility boundaries for a flexible multi-arm multi-stage clinical trial for a normally distributed endpoint with known variance. We show that the boundaries control the familywise error rate in the strong sense. The method is applicable for any number of treatment arms, number of stages and number of patients per treatment per stage. It can be used for a wide variety of boundary types or rules derived from α-spending functions. Additionally, we show how sample size can be computed under a least favourable configuration power requirement and derive formulae for expected sample sizes.

KW - Clinical trial

KW - Dunnett test

KW - Familywise error rate

KW - Treatment selection

U2 - 10.1093/biomet/ass002

DO - 10.1093/biomet/ass002

M3 - Journal article

VL - 99

SP - 494

EP - 501

JO - Biometrika

JF - Biometrika

SN - 0006-3444

IS - 2

ER -