Table 1.
Two-way mixed-effect analysis of variance (ANOVA) model
Case 3 model of McGraw and Wong [6, p34]: | Two-way mixed model with interaction![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Source of variance | df | MS | Expected components in MS | |
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Between patients | n − 1 | MS P |
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Within patients | ||||
Between time points | k − 1 | MS T |
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Error (p × t) | (n − 1)(k − 1) | MS E |
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ICC (A, 1) of McGraw and Wong [6, p 35] =![]() |
A absolute agreement, E, e error, k number of time points, MS mean squares, n number of patients in the test–retest evaluation, P, p patients, T, t time points
In a typical test–retest assessment with two time points, k is 2 in the above ANOVA model and ICC (A, 1) formula. SAS Proc GLM and Proc Mixed can be used to generate the components needed to compute the intraclass correlation coefficient (ICC). Programming information is available upon request to the corresponding author, and a publicly available macro for computing ICCs in the notational system of Shrout and Fleiss can be found at the SAS website http://support.sas.com/kb/25/031.html
The confidence interval formula of ICC (A, 1) for case 3 model of McGraw and Wong [6] can be found on page 41 of the original paper