A maybe trivial and stupid question: In the case of a lm or glm fit, it is quite informative (to me) to have a look to the null deviance and the residual deviance of a model. This is generally provided in the print method or the summary, eg:
Null Deviance: 658.8 Residual Deviance: 507.3 and (a bit simpled minded) I like to think that the proportion of deviance 'explained' by the model is (658.8-507.3)/658.8 = 23% In the case of lme models, is it possible and reasonable to try and get the: - null deviance - the total deviance due to the the random effect(s) - the residual deviance? With the idea that Null deviance = Fixed effects + Random Effects + Residuals If yes how to do it ? A lme object provides the following: > names(glm6) [1] "modelStruct" "dims" "contrasts" "coefficients" [5] "varFix" "sigma" "apVar" "logLik" [9] "numIter" "groups" "call" "method" [13] "fitted" "residuals" "fixDF" "family" so no $null.deviance and $deviance elements as in glm objects... I tried to find out an answer on R-help & Pineihro & Bates (2000). Partial success only: - null deviance: Response: possibly yes: see http://tolstoy.newcastle.edu.au/R/help/05/12/17796.html (Spencer Graves). The (null?) deviance is -2*logLik(mylme), but a personnal trial with some glm objects did not led to the same numbers that the one given by the print.glm method... - the deviance due to the the random effect(s). I was supposing that the coefficients given by ranef(mylme) may be an entry... but beyond this, I guess those coefficients must be weighed in some way... which is a far beyond my capacities in this matter... - residual deviance. I was supposing that it may be sum(residuals(mylme)^2). With some doubts as far as I feel that I am thinking sum of squares estimation in the context of likelihood and deviance estimations... So most likely irrelevant. Moreover, in the case I was exploring, this quantity is much larger than the null deviance computed as above... Any hint appreciated, Patrick Giraudoux ______________________________________________ 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