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Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio

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Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio. / Siqueira, Arminda Lucia; Todd, Susan; Whitehead, Anne.

In: Statistical Methods in Medical Research, Vol. 24, No. 4, 08.2015, p. 453-461.

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Siqueira, Arminda Lucia ; Todd, Susan ; Whitehead, Anne. / Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio. In: Statistical Methods in Medical Research. 2015 ; Vol. 24, No. 4. pp. 453-461.

Bibtex

@article{2e305fa3ab274c29a0b132cc0801ff65,
title = "Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio",
abstract = "This paper presents an approximate closed form sample size formula for determining non-inferiority in active-control trials with binary data. We use the odds-ratio as the measure of the relative treatment effect, derive the sample size formula based on the score test and compare it with a second, well-knownformula based on the Wald test. Both closed form formulae are compared with simulations based on the likelihood ratio test. Within the range of parameter values investigated, the score test closed form formula is reasonably accurate when non-inferiority margins are based on odds-ratios of about 0.5 orabove and when the magnitude of the odds ratio under the alternative hypothesis lies between about 1and 2.5. The accuracy generally decreases as the odds ratio under the alternative hypothesis moves upwards from 1. As the non-inferiority margin odds ratio decreases from 0.5, the score test closed form formula increasingly overestimates the sample size irrespective of the magnitude of the odds ratio under the alternative hypothesis. The Wald test closed form formula is also reasonably accurate in the cases where the score test closed form formula works well. Outside these scenarios, the Wald test closed form formula can either underestimate or overestimate the sample size, depending on the magnitude of the non-inferiority margin odds ratio and the odds ratio under the alternative hypothesis. Although neither approximation is accurate for all cases, both approaches lead to satisfactory sample size calculation for non-inferiority trials with binary data where the odds ratio is the parameter of interest.",
keywords = "binary data, non-inferiority, odds ratio, sample size",
author = "Siqueira, {Arminda Lucia} and Susan Todd and Anne Whitehead",
year = "2015",
month = aug,
doi = "10.1177/0962280214520729",
language = "English",
volume = "24",
pages = "453--461",
journal = "Statistical Methods in Medical Research",
issn = "0962-2802",
publisher = "SAGE Publications Ltd",
number = "4",

}

RIS

TY - JOUR

T1 - Sample size considerations in active-control non-inferiority trials with binary data based on the odds ratio

AU - Siqueira, Arminda Lucia

AU - Todd, Susan

AU - Whitehead, Anne

PY - 2015/8

Y1 - 2015/8

N2 - This paper presents an approximate closed form sample size formula for determining non-inferiority in active-control trials with binary data. We use the odds-ratio as the measure of the relative treatment effect, derive the sample size formula based on the score test and compare it with a second, well-knownformula based on the Wald test. Both closed form formulae are compared with simulations based on the likelihood ratio test. Within the range of parameter values investigated, the score test closed form formula is reasonably accurate when non-inferiority margins are based on odds-ratios of about 0.5 orabove and when the magnitude of the odds ratio under the alternative hypothesis lies between about 1and 2.5. The accuracy generally decreases as the odds ratio under the alternative hypothesis moves upwards from 1. As the non-inferiority margin odds ratio decreases from 0.5, the score test closed form formula increasingly overestimates the sample size irrespective of the magnitude of the odds ratio under the alternative hypothesis. The Wald test closed form formula is also reasonably accurate in the cases where the score test closed form formula works well. Outside these scenarios, the Wald test closed form formula can either underestimate or overestimate the sample size, depending on the magnitude of the non-inferiority margin odds ratio and the odds ratio under the alternative hypothesis. Although neither approximation is accurate for all cases, both approaches lead to satisfactory sample size calculation for non-inferiority trials with binary data where the odds ratio is the parameter of interest.

AB - This paper presents an approximate closed form sample size formula for determining non-inferiority in active-control trials with binary data. We use the odds-ratio as the measure of the relative treatment effect, derive the sample size formula based on the score test and compare it with a second, well-knownformula based on the Wald test. Both closed form formulae are compared with simulations based on the likelihood ratio test. Within the range of parameter values investigated, the score test closed form formula is reasonably accurate when non-inferiority margins are based on odds-ratios of about 0.5 orabove and when the magnitude of the odds ratio under the alternative hypothesis lies between about 1and 2.5. The accuracy generally decreases as the odds ratio under the alternative hypothesis moves upwards from 1. As the non-inferiority margin odds ratio decreases from 0.5, the score test closed form formula increasingly overestimates the sample size irrespective of the magnitude of the odds ratio under the alternative hypothesis. The Wald test closed form formula is also reasonably accurate in the cases where the score test closed form formula works well. Outside these scenarios, the Wald test closed form formula can either underestimate or overestimate the sample size, depending on the magnitude of the non-inferiority margin odds ratio and the odds ratio under the alternative hypothesis. Although neither approximation is accurate for all cases, both approaches lead to satisfactory sample size calculation for non-inferiority trials with binary data where the odds ratio is the parameter of interest.

KW - binary data

KW - non-inferiority

KW - odds ratio

KW - sample size

U2 - 10.1177/0962280214520729

DO - 10.1177/0962280214520729

M3 - Journal article

VL - 24

SP - 453

EP - 461

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

SN - 0962-2802

IS - 4

ER -