Confidence intervals for proportion ratios of stratified correlated bilateral data

In stratified bilateral studies, responses from two paired body parts are correlated. Confidence intervals (CIs), which reveal various features of the data, should take the correlations into account. In this article, five CI methods (sample-size weighted naïve Maximum likelihood estimation (MLE)-bas...

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Bibliographic Details
Published in:Journal of biopharmaceutical statistics 2019-01, Vol.29 (1), p.203-225
Main Authors: Zhuang, Tingting, Tian, Guo-Liang, Ma, Chang-Xing
Format: Article
Language:English
Subjects:
Anti-Bacterial Agents - therapeutic use
Biostatistics - methods
Collagen - therapeutic use
Computer Simulation
Confidence interval
Confidence Intervals
Data Interpretation, Statistical
equal correlation coefficients model
Humans
Likelihood Functions
Monte Carlo Method
Otitis Media with Effusion - drug therapy
Otitis Media with Effusion - microbiology
proportion ratios
Randomized Controlled Trials as Topic - statistics & numerical data
Research Design - statistics & numerical data
Scleroderma, Diffuse - drug therapy
Scleroderma, Diffuse - pathology
stratified bilateral data
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Summary:In stratified bilateral studies, responses from two paired body parts are correlated. Confidence intervals (CIs), which reveal various features of the data, should take the correlations into account. In this article, five CI methods (sample-size weighted naïve Maximum likelihood estimation (MLE)-based Wald-type CI, complete MLE-based Wald-type CI, profile likelihood CI, MLE-based score CI and pooled MLE-based Wald-type CI) are derived for proportion ratios under the assumption of equal correlation coefficient within each stratum. Monte Carlo simulation shows that the complete MLE-based Wald-type CI approach generally produces the shortest mean interval width and satisfactory empirical coverage probability with close form solution; while the profile likelihood CI and the MLE-based score CI provide preferred ratio of non coverage probability and are more symmetric. Two real examples are used to demonstrate the performance of the proposed methods.
ISSN:1054-3406
1520-5711
DOI:10.1080/10543406.2018.1489405