L-statistics of absolute differences for quantifying the agreement between two variables

Elahe Tashakor, Vernon M. Chinchilli

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


In many clinical studies, Lin’s (1989) concordance correlation coefficient (CCC) is a popular measure of agreement for continuous outcomes. Most commonly, it is used under the assumption that data are normally distributed. However, in many practical applications, data are often skewed and/or thick-tailed. King and Chinchilli (2001) proposed robust estimation methods of alternative CCC indices, and we propose an approach that extends the existing methods of robust estimators by focusing on functionals that yield robust L-statistics. We provide two data examples to illustrate the methodology, and we discuss the results of computer simulation studies that evaluate statistical performance.

Original languageEnglish (US)
Pages (from-to)174-188
Number of pages15
JournalJournal of Biopharmaceutical Statistics
Issue number1
StatePublished - Jan 2 2019

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)


Dive into the research topics of 'L-statistics of absolute differences for quantifying the agreement between two variables'. Together they form a unique fingerprint.

Cite this