A comparative study of matched pair designs with two binary endpoints

Yuanyuan Jiang; Jin Xu

doi:10.1177/0962280215601136

A comparative study of matched pair designs with two binary endpoints

Yuanyuan Jiang
, Jin Xu^*

^*Corresponding author for this work

School of Statistics

East China Normal University

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

We study matched pair designs with two binary endpoints under three different approaches. Power approximation and sample size calculation are derived under these situations and facilitated by R programs. An adaptive design with sample size re-estimation is also presented. Through extensive simulations, we provide general guidelines for practitioners to choose the best approach according to the ranges of the interested parameters in the sense of feasibility and robustness. Application to a cancer chemotherapy trial is illustrated.

Original language	English
Pages (from-to)	2526-2542
Number of pages	17
Journal	Statistical Methods in Medical Research
Volume	26
Issue number	6
DOIs	https://doi.org/10.1177/0962280215601136
State	Published - 1 Dec 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Binary endpoint
equivalence
matched pair design
non-inferiority

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10.1177/0962280215601136

Cite this

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abstract = "We study matched pair designs with two binary endpoints under three different approaches. Power approximation and sample size calculation are derived under these situations and facilitated by R programs. An adaptive design with sample size re-estimation is also presented. Through extensive simulations, we provide general guidelines for practitioners to choose the best approach according to the ranges of the interested parameters in the sense of feasibility and robustness. Application to a cancer chemotherapy trial is illustrated.",

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AB - We study matched pair designs with two binary endpoints under three different approaches. Power approximation and sample size calculation are derived under these situations and facilitated by R programs. An adaptive design with sample size re-estimation is also presented. Through extensive simulations, we provide general guidelines for practitioners to choose the best approach according to the ranges of the interested parameters in the sense of feasibility and robustness. Application to a cancer chemotherapy trial is illustrated.

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KW - matched pair design

KW - non-inferiority

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A comparative study of matched pair designs with two binary endpoints

Abstract

UN SDGs

Keywords

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