title: A Bayesian estimate of the concordance correlation coefficient with skewed data.
abstract: Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real-life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network.
authors.affiliation: Merck & Co., Inc., Rahway, NJ, USA.
authors.forename: Dai
authors.initials: D
authors.lastname: Feng
authors.affiliation: Merck & Co., Inc., Rahway, NJ, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Baumgartner
authors.affiliation: Merck & Co., Inc., Rahway, NJ, USA.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Svetnik
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data; D006801:Humans; D006993:Hypnotics and Sedatives / Q000627:therapeutic use; D015233:Models, Statistical; D012107:Research Design / Q000706:statistics & numerical data*; D012890:Sleep / Q000187:drug effects; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D006993:Hypnotics and Sedatives
keywords: Bayesian MCMC; R programming language; bootstrap; concordance correlation coefficient; lognormal-normal mixed-effects model; skewed data