I am getting a hard time to go around this and I am not sure my interpretation is correct. I have several models that look like this:
change | trials ~ treatmentA + treatmentB + treatmentC + (1|person)
I would like to correctly interpret my group-level estimate (random effect) and its derived intraclass correlation coefficient (ICC). By definition, the ICC can be interpreted as “the proportion of the variance explained by the grouping structure in the population”. The ICC is calculated by dividing the random effect variance, σ2i, by the total variance, i.e. the sum of the random effect variance and the residual variance, σ2ε.
Would an ICC close to 1 indicate high consistency of response across treatments within the same person, while an ICC close to zero refer to an heterogeneous intra-patient response?
Could you recommend me some literature or provide me a bit more insight on this?
I am not interested on 'siblings studies' or 'sample replicability'... I would rather know if I could use the ICC measure for estimating how similar or divergent are patients in regards to the response in each of the models.
Thanks in advance! Cheers