Using the coefficient of correlation in method-comparison studies.
The coefficient of correlation (R) is one of the most commonly computed statistics in method-comparison studies. Usually, it is simply quoted without interpretation. In this paper, we show how R may be used to detect interference, nonlinearity, and misuse of the imprecision components. Specifically, one may precisely predict what R should be by considering the imprecisions of the two methods being compared, even before the comparison is performed. When the actual R disagrees with the predicted R, then one of the mentioned effects is present. We also describe a statistical test to detect these effects at the P = 0.05 level, then evaluate this test by using computer simulation and present two examples of its use. We also present the theory underlying the usage of R, including how R is affected by the distribution and range of the data, by the joint imprecisions of the methods being compared, by the sample size, and by the randomness of the specimen-selection process.
D001322:Autoanalysis; D001786:Blood Glucose / Q000032:analysis; D002624:Chemistry, Clinical / Q000379:methods*; D006801:Humans; D010710:Phosphates / Q000097:blood; D013223:Statistics as Topic
D001786:Blood Glucose; D010710:Phosphates