Comparison of Concordance Correlation Coefficient Estimating Approaches with Skewed Data |
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| Authors: | Josep L Carrasco Lluis Jover Tonya S King Vernon M Chinchilli |
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| Institution: | 1. Biostatistics, Public Health Department , University of Barcelona , Barcelona, Spain jlcarrasco@ub.edu;3. Biostatistics, Public Health Department , University of Barcelona , Barcelona, Spain;4. Department of Health Evaluation Sciences , Penn State University , Pennsylvania, USA |
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| 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. |
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| Keywords: | Concordance correlation coefficient Generalized estimating equations Linear mixed model Log-normal distribution Skewed data U-statistics Variance components |
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