computer methods and programs in biomedicine 88 ( 2 0 0 7 ) 62–74 journal homepage: www.intl.elsevierhealth.com/journals/cmpb Computer programs for the concordance correlation coefficient Sara B. Crawford a,* , Andrzej S. Kosinski b , Hung-Mo Lin c , John M. Williamson a , Huiman X. Barnhart b a Division of Parasitic Diseases, Centers for Disease Control and Prevention, 4770 Buford Highway NE (MS-F22), Atlanta, GA 30341, United States b Department of Biostatistics and Bioinformatics and Duke Clinical Research Institute, Duke University, PO Box 17969, Durham, NC 27715, United States c Department of Health Evaluation Sciences, Penn State College of Medicine, A210 600 Centerview Dr., Hershey, PA 17033, United States article info Article history: Received 18 December 2006 Received in revised form 5 July 2007 Accepted 5 July 2007 Keywords: Agreement Bootstrap Concordance correlation coefficient Dependence Reproducibility abstract The CCC macro is presented for computation of the concordance correlation coefficient (CCC), a common measure of reproducibility. The macro has been produced in both SAS and R, and a detailed presentation of the macro input and output for the SAS program is included. The macro provides estimation of three versions of the CCC, as presented by Lin [L.I.-K. Lin, A concordance correlation coefficient to evaluate reproducibility, Biometrics 45 (1989) 255–268], Barnhart et al. [H.X. Barnhart, J.L. Haber, J.L. Song, Overall concordance correlation coefficient for evaluating agreement among multiple observers, Biometrics 58 (2002) 1020–1027], and Williamson et al. [J.M. Williamson, S.B. Crawford, H.M. Lin, Resampling dependent concordance correlation coefficients, J. Biopharm. Stat. 17 (2007) 685–696]. It also provides bootstrap confidence intervals for the CCC, as well as for the difference in CCCs for both independent and dependent samples. The macro is designed for balanced data only. Detailed explanation of the involved computations and macro variable definitions are provided in the text. Two biomedical examples are included to illustrate that the macro can be easily implemented. © 2007 Elsevier Ireland Ltd. All rights reserved. 1. Introduction In the health sciences, it is often necessary to study the reproducibility of continuous measurements made using a certain diagnostic tool or method. As technology brings forth new tools and methods, we are interested in evaluating the consistency of evaluations made using the new method as well as comparing this measure to the current gold standard if one exists. The concordance correlation coefficient (CCC) provides a means for examining the reproducibility of contin- ∗ Corresponding author. Tel.: +1 770 488 4204. E-mail address: sgv0@cdc.gov (S.B. Crawford). uous measurements made by multiple raters using a single method or by two or more raters using two methods. Sev- eral other reproducibility measures are available, such as the Pearson correlation coefficient, the intraclass correlation coef- ficient [4,5], and the within-subject coefficient of variation [6]. In general, these measures do not address both precision and accuracy as does the concordance correlation coefficient; however, the equivalency and similarities of the intraclass cor- relation coefficient to the concordance correlation coefficient under certain scenarios has been discussed by Nickerson [7], 0169-2607/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.cmpb.2007.07.003