The Intraclass Correlation Coefficient (ICC) can be used to measure the strength of the Inter-Rater agreement in a situation where the evaluation scale is continuous or ordinal. It is suitable for studies with two or more tips. Note that CCI can also be used for test reliability analysis (repeated measurements of the same subject) and intra-rater (several points from the same tips). Note that the model is recommended for two mixed effects pathways and for absolute compliance for both retest testing and intra-rater reliability studies (Koo et al., 206). CCI is strictly defined as the correlation between a subject`s measurements in repeated tests.1 Intuitively, if this correlation is high, it means that the neuroimaging modality provides very similar measurements in the tests (or test and retested if k-2), an indicator of high reliability. A more technical interpretation of CCI is that it is a measure of the variance due to subjects2 in overall variance. According to this interpretation, the CCI can continue to be divided into two categories: as a measure of the (absolute) test agreement and as a measure of test coherence.2 Equations (6) and (7) are the expressions of both definitions: second, we must correctly interpret CCIs in terms of absolute consistency and consistency between the measures of repeated tests. According to Property 1, ICC (2.1) /ICC (2.k) and ICC (3.1)/ICC (3.k) have different interpretations for measuring the absolute consistency between the tests and their consistency. From a technical point of view, the two interpretations differ as to whether the difference between tests is taken into account in the reliability assessment; Absolute agreement measures involve discrepancies between tests, while coherence measures do not. Therefore, ICC (3.1)/ICC (3.k) should be used in cases where variance between tests is an irrelevant source of variation.2 Is an example if the problem is not the absolute measurements of the subjects in each test, but their relative differences in the test (as a result, the difference of each measure relative to the average of all subjects is used in the analysis). We are now turning to the consistency version of the intraclassical correlation coefficient of the population defined with Model 3 in the same way as for Model 2, i.e. as (27) reminder that size 2 – 2 , Eq (27) is identical to the ICC population, called McGraw and Wong`s “Case 3A” .
In fact, Eq (27) is identical to Eq (13), and with Eq (25), there is again the ICC formula (C,1) of Eq (14), also in agreement with McGraw and Wong . This result is also achieved by Bartko , with the additional assumption that the notion of interaction is negligible. This hypothesis has not been used here. In statistics, intraclassical correlation or intraclassical correlation coefficient (CCI)  is a descriptive statistic that can be used when quantitative measurements are made on group-organized units.
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