Homogeneity test and sample size of risk difference for stratified unilateral and bilateral data

Unilateral or bilateral paired data are often encountered in medical studies. It is natural to analyze such data by combining them. In the article, the homogeneity test of risk difference and sample size determination are investigated based on the stratified uni- and bilateral paired data. Under Dal...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 53; no. 9; pp. 4209 - 4232
Main Authors Sun, Shuman, Li, Zhiming, Jiang, Haijun
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 01.09.2024
Taylor & Francis Ltd
Subjects
Asymptotic methods
Dallal's model
Homogeneity
Homogeneity test
Iterative algorithms
Monte Carlo simulation
Ophthalmology
Risk difference
Sample size
Size determination
Statistical methods
Statistical tests
Stratified data
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Summary:Unilateral or bilateral paired data are often encountered in medical studies. It is natural to analyze such data by combining them. In the article, the homogeneity test of risk difference and sample size determination are investigated based on the stratified uni- and bilateral paired data. Under Dallal's model, we propose six statistical tests and eight sample size methods. Monte Carlo simulations show that the score test behaves well in various parameter settings. Wald-type test always has higher empirical powers. Iterative algorithm and asymptotical method are introduced to estimate sample sizes, and the estimated powers of the former are closer to the desired power than that of the latter. An ophthalmology example is used to demonstrate the performance of the proposed methods.
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2022.2142240