Rich Ulrich wrote: > For contrasting 2 raters, I like using a paired t-test and the > corresponding interclass correlation. That shows you both > the main pieces of information, without confusing them or > confounding them at all. You get r to measure parallelism; > you get t to measure mean-difference.
Lin has discussed the shortcomings of the t-test for assessing concordance between raters (Biometrics, 1989, 45, 255-268). Among other things, the paired t-test fails to detect poor agreement in pairs of data such as (1,3)(2,3)(3,3)(4,3)(5,3). Pearson correlation coefficient can be a good starting point for detecting lack of agreement. But, a high r doesn't necessarily indicate agreement. As a follow-up, Lin's concordance correlation coefficient or the Bradley-Blackwood procedure can be useful supplements. SR Millis . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
