Comparison of concordance correlation coefficient estimating approaches with skewed data

J Biopharm Stat. 2007;17(4):673-84. doi: 10.1080/10543400701329463.

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.

Publication types

  • Comparative Study

MeSH terms

  • Alcohol Drinking
  • Algorithms
  • Analysis of Variance
  • Biometry / methods*
  • Computer Simulation
  • Confidence Intervals
  • Humans
  • Linear Models
  • Models, Statistical*
  • Reproducibility of Results
  • Risk Assessment / statistics & numerical data
  • Statistical Distributions
  • Surveys and Questionnaires