Shinichi Nakagawa <S.Nakagawa <at> sheffield.ac.uk> writes: ... > I am a little confused which one to trust and use. Or there are no easy form > to do this? I am guessing formula would change depending on what distribution > you use and what link function as well? I want to calculate icc from GLMM with > Poisson with log link function and also binomial with logit function. Could > anybody help me please?
Yes, you are right that ICC depends on assumed data distribution. While ICC is very handy in linear models it is not the case in GLMM. I suggest you take a look at the references bellow. There is also some online material by the same authors. Additionally, I remember that there were lively discussions about ICC on "multilevel" list at http://www.jiscmail.ac.uk/lists/multilevel.html Best wishes, Gregor @Article{Goldstein:2002, author = {Goldstein, H. and Browne, W. and Rabash, J.}, title = {Partitioning variation in multilevel models}, journal = {Understanding Statistics}, year = {2002}, volume = {1}, number = {4}, pages = {223--231}, keywords = {variance ratio, variance partition coefficient, intra-unit correlation, intra-class correlation, normal models, discrete models, random coefficient models} } @Article{Browne:2005, author = {Browne, W. J. and Subramanian, S. V. and Jones, K. and Goldstein, H.}, title = {Variance partitioning in multilevel logistic models that exhibit overdispersion}, journal = {J. R. Stat. Soc. A Stat. Soc.}, year = {2005}, volume = {168}, number = {3}, pages = {599--613}, doi = {10.1111/j.1467-985X.2004.00365.x}, checked = {[2006-04-16]}, keywords = {heritability, ratios, intra-class correlation, intra-unit correlation, simulation, linearization, latent variable approach}, } ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.