Literature DB >> 20183448

Sample size for testing difference between two proportions for the bilateral-sample design.

Shi-Fang Qiu1, Nian-Sheng Tang, Man-Lai Tang, Yan-Bo Pei.   

Abstract

In this article, we consider approximate sample size formulas for testing difference between two proportions for bilateral studies with binary outcomes. Sample size formulas are derived to achieve a prespecified power of a statistical test at a prechosen significance level. Four statistical tests are considered. Simulation studies are conducted to investigate the accuracy of various formulas. In general, the sample size formula for Rosner's statistic based on the dependence assumption is highly recommended in the sense that its actual power is satisfactorily close to the desired power level. An example from an otolaryngological study is used to demonstrate the proposed methodologies.

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Year:  2009        PMID: 20183448     DOI: 10.1080/10543400903105372

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  3 in total

1.  Objective Bayesian Inference for Bilateral Data.

Authors:  Cyr Emile M'lan; Ming-Hui Chen
Journal:  Bayesian Anal       Date:  2015-01-28       Impact factor: 3.728

2.  Simultaneous confidence interval construction for many-to-one comparisons of proportion differences based on correlated paired data.

Authors:  Zhengyu Yang; Guo-Liang Tian; Xiaobin Liu; Chang-Xing Ma
Journal:  J Appl Stat       Date:  2020-07-22       Impact factor: 1.416

3.  Statistical tests under Dallal's model: Asymptotic and exact methods.

Authors:  Zhiming Li; Changxing Ma; Mingyao Ai
Journal:  PLoS One       Date:  2020-11-30       Impact factor: 3.240

  3 in total

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