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. 2018 Dec 13;28(4):1029–1033. doi: 10.1007/s11136-018-2076-0

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
Inline graphic, where
Inline graphic: grand mean
Inline graphic difference due to patient i (i = 1, …, n), Inline graphic
Inline graphic difference due to time point j (j = 1, …, k), Inline graphic
Inline graphic interaction between patient i and time point j, Inline graphic and Inline graphic
Inline graphic: random error, Inline graphic
Source of variance df MS Expected components in MS
Between patients n − 1 MS P Inline graphic
Within patients
Between time points k − 1 MS T Inline graphic
Error (p × t) (n − 1)(k − 1) MS E Inline graphic
ICC (A, 1) of McGraw and Wong [6, p 35] =Inline graphic

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