similar to: lme4 and lmeSplines

Dear readers, Is it possible to specify a model y=X %*% beta + Z %*% b ; b=(b_1,..,b_k) and b_i~N(0,v^2) for i=1,..,k that is, a model where the random slopes for different covariates are i.i.d., in lmer() and how? In lme() one needs a constant grouping factor (e.g.: all=rep(1,n)) and would then specify: lme(fixed= y~X, random= list(all=pdIdent(~Z-1)) ) , that?s how it's done in the

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

Hi, I am analysing an experiment that has one fixed (6 conditions) and two random factors (11 subjects, 24 images in the conditions). I read somewhere else that you can also see such a design as a nested experiment with the hierarchy: subjects -> condition -> image. For some analysis I have one respond variable and for others I have more. The response variables are non-normally distributed.

We have published the 2003/3 issue of R News on http://cran.R-project.org/doc/Rnews where you can download the newsletter as PDF or Postscript file. It will propagate to the CRAN mirrors within a day or two. Contents of this issue: Dimensional Reduction for Data Mapping R as a Simulation Platform in Ecological Modelling Using R for Estimating Longitudinal Student Achievement Models lmeSplines

We have published the 2003/3 issue of R News on http://cran.R-project.org/doc/Rnews where you can download the newsletter as PDF or Postscript file. It will propagate to the CRAN mirrors within a day or two. Contents of this issue: Dimensional Reduction for Data Mapping R as a Simulation Platform in Ecological Modelling Using R for Estimating Longitudinal Student Achievement Models lmeSplines

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working