Related Experiment Video
Updated: Jun 19, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
A comparison of methods for the construction of confidence interval for relative risk in stratified matched-pair
Nian-Sheng Tang1, Hui-Qiong Li, Man-Lai Tang
1Department of Statistics, Yunnan University, Kunming, People's Republic of China. nstang@ynu.edu.cn
Abstract:
A stratified matched-pair study is often designed for adjusting a confounding effect or effect of different trails/centers/ groups in modern medical studies. The relative risk is one of the most frequently used indices in comparing efficiency of two treatments in clinical trials. In this paper, we propose seven confidence interval estimators for the common relative risk and three simultaneous confidence interval estimators for the relative risks in stratified matched-pair designs. The performance of the proposed methods is evaluated with respect to their type I error rates, powers, coverage probabilities, and expected widths. Our empirical results show that the percentile bootstrap confidence interval and bootstrap-resampling-based Bonferroni simultaneous confidence interval behave satisfactorily for small to large sample sizes in the sense that (i) their empirical coverage probabilities can be well controlled around the pre-specified nominal confidence level with reasonably shorter confidence widths; and (ii) the empirical type I error rates of their associated test statistics are generally closer to the pre-specified nominal level with larger powers. They are hence recommended. Two real examples from clinical laboratory studies are used to illustrate the proposed methodologies.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Relative Risk
Odds Ratio
The Mantel-Cox Log-Rank Test
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confidence Intervals
A confidence...

