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A combined score test for binary and ordinal endpoints from clinical trials.

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A combined score test for binary and ordinal endpoints from clinical trials. / Whitehead, John; Branson, Michael; Todd, Susan.
In: Statistics in Medicine, Vol. 29, No. 5, 28.02.2010, p. 521-532.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Whitehead, J, Branson, M & Todd, S 2010, 'A combined score test for binary and ordinal endpoints from clinical trials.', Statistics in Medicine, vol. 29, no. 5, pp. 521-532. https://doi.org/10.1002/sim.3822

APA

Vancouver

Whitehead J, Branson M, Todd S. A combined score test for binary and ordinal endpoints from clinical trials. Statistics in Medicine. 2010 Feb 28;29(5):521-532. doi: 10.1002/sim.3822

Author

Whitehead, John ; Branson, Michael ; Todd, Susan. / A combined score test for binary and ordinal endpoints from clinical trials. In: Statistics in Medicine. 2010 ; Vol. 29, No. 5. pp. 521-532.

Bibtex

@article{f4ba7785e4b64fc9a0ef7bf7f1fc0376,
title = "A combined score test for binary and ordinal endpoints from clinical trials.",
abstract = "There is growing interest, especially for trials in stroke, in combining multiple endpoints in a single clinical evaluation of an experimental treatment. The endpoints might be repeated evaluations of the same characteristic or alternative measures of progress on different scales. Often they will be binary or ordinal, and those are the cases studied here. In this paper we take a direct approach to combining the univariate score statistics for comparing treatments with respect to each endpoint. The correlations between the score statistics are derived and used to allow a valid combined score test to be applied. A sample size formula is deduced and application in sequential designs is discussed. The method is compared with an alternative approach based on generalized estimating equations in an illustrative analysis and replicated simulations, and the advantages and disadvantages of the two approaches are discussed.",
keywords = "binary responses • generalized estimating equations • global tests • ordered categorical responses • score statistics • stroke trials",
author = "John Whitehead and Michael Branson and Susan Todd",
year = "2010",
month = feb,
day = "28",
doi = "10.1002/sim.3822",
language = "English",
volume = "29",
pages = "521--532",
journal = "Statistics in Medicine",
issn = "1097-0258",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

RIS

TY - JOUR

T1 - A combined score test for binary and ordinal endpoints from clinical trials.

AU - Whitehead, John

AU - Branson, Michael

AU - Todd, Susan

PY - 2010/2/28

Y1 - 2010/2/28

N2 - There is growing interest, especially for trials in stroke, in combining multiple endpoints in a single clinical evaluation of an experimental treatment. The endpoints might be repeated evaluations of the same characteristic or alternative measures of progress on different scales. Often they will be binary or ordinal, and those are the cases studied here. In this paper we take a direct approach to combining the univariate score statistics for comparing treatments with respect to each endpoint. The correlations between the score statistics are derived and used to allow a valid combined score test to be applied. A sample size formula is deduced and application in sequential designs is discussed. The method is compared with an alternative approach based on generalized estimating equations in an illustrative analysis and replicated simulations, and the advantages and disadvantages of the two approaches are discussed.

AB - There is growing interest, especially for trials in stroke, in combining multiple endpoints in a single clinical evaluation of an experimental treatment. The endpoints might be repeated evaluations of the same characteristic or alternative measures of progress on different scales. Often they will be binary or ordinal, and those are the cases studied here. In this paper we take a direct approach to combining the univariate score statistics for comparing treatments with respect to each endpoint. The correlations between the score statistics are derived and used to allow a valid combined score test to be applied. A sample size formula is deduced and application in sequential designs is discussed. The method is compared with an alternative approach based on generalized estimating equations in an illustrative analysis and replicated simulations, and the advantages and disadvantages of the two approaches are discussed.

KW - binary responses • generalized estimating equations • global tests • ordered categorical responses • score statistics • stroke trials

U2 - 10.1002/sim.3822

DO - 10.1002/sim.3822

M3 - Journal article

VL - 29

SP - 521

EP - 532

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 1097-0258

IS - 5

ER -