Lin's Concordance Correlation Coefficient (CCC)
Evaluates whether two measurement methods (or two measurements) agree. Pearson r only looks at "linear correlation" and cannot detect systematic bias; CCC also considers whether points fall on the 45° line, making it more suitable for methodological agreement and complementary to Bland-Altman. It gives CCC, Pearson r, the bias-correction factor Cb and a 95% CI.
① Paste paired data
One pair per line, two columns for the method X and method Y measurements (separated by space/Tab/comma).
How to use & methodology
How does CCC differ from Pearson r?
Pearson r only measures whether two sets of numbers are linearly correlated; even if Y is always higher than X (systematic bias), r can still be 1. CCC additionally requires points to fall on the 45° identity line, reflecting both correlation and systematic bias, so it is better suited to judging 'whether two methods agree'.
How do CCC and Bland-Altman work together?
CCC gives a single summary agreement number, convenient for comparison and reporting; the Bland-Altman plot visually shows the size of the bias, whether it varies with the measurement value, and the 95% limits of agreement. Methodological agreement studies often use both.
How do I read Cb (bias-correction factor)?
Cb measures accuracy — how far the data depart from the 45° line, ranging 0–1, with 1 meaning no systematic bias. CCC = r × Cb: if r is high but CCC is clearly lower, the problem is systematic bias (small Cb), not random scatter.
How many samples are needed?
At least 3 pairs, but methodological agreement evaluation usually recommends dozens or more for a stable estimate and a narrower CI. This tool's CI uses Lin's (1989) z-transform approximation.