Abstract
The concordance correlation coefficient (CCC) is a popular index for measuring the reproducibility of continuous variables. We examine two resampling approaches, permutation testing and the bootstrap, for conducting hypothesis tests on dependent CCCs obtained from the same sample. Resampling methods are flexible, require minimal marginal and joint distributional assumptions, and do not rely on large sample theory. However, the permutation test requires a restrictive assumption (exchangeability) which limits its applicability in this situation. Simulation results indicate that inference based on the bootstrap is valid, although type-I error rates are inflated for small sample sizes (≈30). For illustration we analyze data from a carotid stenosis screening study.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
