Using variance components of lmer for ICC computation in reliability study
Well no, you?re specification is not right because your variable is not continuous as you note. Continuous means it is a real number between -Inf/Inf and you have boundaries between 1 and 10. So, you should not be using a linear model assuming the outcome is continuous.
On 6/14/18, 11:16 AM, "Bernard Liew" <B.Liew at bham.ac.uk> wrote:
Dear Community, I am doing a reliability study, using the methods of https://www.ncbi.nlm.nih.gov/pubmed/28505546. I have a question on the lmer formulation and the use of the variance components. Background: I have 20 subjects, 2 fixed raters, 2 testing sessions, and 10 trials per sessions. my dependent variable is a continuous variable (scale 1-10). Sessions are nested within each subject-assessor combination. I desire a ICC (3) formulation of inter-rater and inter-session reliability from the variance components. My lmer model is: lmer (dv ~ rater + (1|subj) + (1|subj:session), data = df) Question: 1. is the model formulation right? and is my interpretation of the variance components for ICC below right? 2. inter-rater ICC = var (subj) / (var(subj) + var (residual)) # I read that the variation of raters will be lumped with the residual 3. inter-session ICC =( var (subj) + var (residual)) /( var (subj) + var (subj:session) + var (residual)) some simulated data: df = expand.grid(subj = c(1:20), rater = c(1:2), session = c(1:2), trial = c(1:10)) df$vas = rnorm (nrow (df_sim), mean = 3, sd = 1.5) I appreciate the kind response. Kind regards, Bernard [[alternative HTML version deleted]]
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