[R] fitting several lme sistematically

Dear R-list, I have a data set (in the following example called "a") which have: one "subject indicator" variable (called "id") three dependent variables (varD, varE, var F) three independent variables (varA, varB, varC) I want to fit 9 lme models, one per posible combination (DA, DB, DC, E

[R] Deviance explined in GAMM, library mgcv

logLik for the saturated model is not available. Any suggestions on how to obtain the deviance explained when a gamm is fitted when the typical default gauusian model is fitted? Or alternavely, are the R^2 derived from a gam model and a gamm model comparable? Thanks a lot in advance, Berta

Re: [R] fit.contrast and interaction terms

ng with the d.f. (it seems that narrower conf. int than expected are obtained). Is it a wrong conclusion to interpretate the p-values? Is there another way to adjuts this, or it is just inappropriate to do this type of contrast? Thanks a lot in advance! Berta SMALL EXPAMPLE library(gmodels) set.

[R] fit.contrast and interaction terms

r a continuous variable? Or it is not possible to do so, and I have to contrast both (difference of intercepts and difference of slopes separately) and obtain a global conclussion? Thanks a lot in advance, Berta [[alternative HTML version deleted]] ___