Assessing agreement with intraclass correlation coefficient and concordance correlation coefficient for data with repeated measures
Chia-Cheng Chen and
Huiman X. Barnhart
Computational Statistics & Data Analysis, 2013, vol. 60, issue C, 132-145
Abstract:
The intraclass correlation coefficient and the concordance correlation coefficient are two popular scaled indices for assessing the closeness between observers who make measurements for quantitative responses. These two indices are usually based on subject and observer effects only, and therefore we cannot use these indices if the observer produces repeated measurements rather than replicated readings. In this paper, we consider not only subject and observer effects, but also time effects for data with repeated measurements since it is difficult to obtain the true replications in practice. We compare these two agreement indices for different combinations of random or fixed effects of observer and time. Finally, we use image data of 2D-echocardiograms to illustrate the proposed methodology and the comparison of these two indices. If there is a need to choose between these two indices for repeated measurements, we recommend to use the new concordance correlation coefficient since it does not need ANOVA assumptions.
Keywords: Intraclass correlation coefficient; Concordance correlation coefficient; Repeated measurements; Mixed effects (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947312003957
Full text for ScienceDirect subscribers only.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:60:y:2013:i:c:p:132-145
DOI: 10.1016/j.csda.2012.11.004
Access Statistics for this article
Computational Statistics & Data Analysis is currently edited by S.P. Azen
More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().