Comparison of concordance correlation coefficient estimating approaches with skewed data

Josep L. Carrasco, Lluis Jover, Tonya S. King, Vernon M. Chinchilli

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)673-684
Number of pages12
JournalJournal of Biopharmaceutical Statistics
Issue number4
StatePublished - Jul 1 2007

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)


Dive into the research topics of 'Comparison of concordance correlation coefficient estimating approaches with skewed data'. Together they form a unique fingerprint.

Cite this