title: Comparison of concordance correlation coefficient estimating approaches with skewed data.
abstract: The concordance correlation coefficient (CCC) is an index that assesses the agreement between continuous measures made by different observers. At least four methods are used to estimate the CCC: two (Lin's method, Variance Components) which are defined on the basis that data are normally distributed, and the two others (U-statistics, GEE) which do not assume any particular distribution of the data. Here the four methods are compared with skewed data from a model in which the subject means follow a log-normal distribution while the within-subject variability is assumed to be normally distributed. An example of alcohol consumption is considered and a simulation study is performed.
authors.affiliation: Biostatistics, Public Health Department, University of Barcelona, Barcelona, Spain. jlcarrasco@ub.edu
authors.forename: Josep L
authors.initials: JL
authors.lastname: Carrasco
authors.forename: Lluis
authors.initials: L
authors.lastname: Jover
authors.forename: Tonya S
authors.initials: TS
authors.lastname: King
authors.forename: Vernon M
authors.initials: VM
authors.lastname: Chinchilli
mesh_terms: D000428:Alcohol Drinking; D000465:Algorithms; D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D016001:Confidence Intervals; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000706:statistics & numerical data; D016008:Statistical Distributions; D011795:Surveys and Questionnaires