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# Intraclass correlation coefficient r lme

The** intraclass correlation coefficient** (ICC) (Fleiss, 1986) is estimated using a** linear mixed** model with subjects (cluster) random effect and random error as components. The effects are assumed to follow Normal distributions with variances Sa and.

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Reference Therneau 2018) package and model M 3 using the **lme** function of the nlme (Pinheiro et al., Reference Pinheiro, Bates, DebRoy and Sarkar 2017) package. **intraclass correlation coefficient** ( ) is the ratio of therapist variance to total variance: I When only post-treatment scores (y) are available, the variance estimates are generated as follows.

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**Intraclass correlations** (i.e., generalizability coefficients) The relative **intraclass correlation** for the situation effect ( ρ ˆ S − relative) is the degree to which the pattern of differences among situations is consistent across people. The general case is (see Table 4 ): (21) ρ ˆ S − relative = C ¯ S V ¯ S.. This is an introduction to using mixed models in **R**.

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A **LME** could be used to calculate the **intraclass** **correlation** **coefficient** (ICC) as a measure of concordance of pixel intensity in between left and right Side . Can anybody help me with the correct formula, i.e. do you have to include variance component estimator for level 1 ("Dog"), too?. 12.4.1.1 Intercept-only model (model 1) and **intraclass** **correlation**.

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The concordance **correlation coefficient** is estimated using the appropriate **intraclass correlation coefficient** (see Carrasco et al, 2009; Carrasco et al, 2013). The variance components The variance components estimates are obtained from a linear mixed model (LMM) estimated by restricted maximum likelihood.

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