hello!
this is a question, how can i specify the random part in the GLMM-call
(of the lme4 library) for compound matrices just in the the same way as
they defined in the lme-Call (of the nlme library). For example
i would just need
random=list(my.Subject=pdBlocked(list(pdIdent(~... , ...),pdIdent(~... ,
...))))
this specification , if i also attach library(nlme) , is not
accepted in the GLMM-call, though the simple form
random=list(my.Subject=pdIdent(~...,...))
is accepted.
what is the analogous of pdBlocked & Co from nlme in lme4?
thanks for replay
>>>>> "Pavel" == Pavel Khomski <pkhomski at wiwi.uni-bielefeld.de> >>>>> on Tue, 08 Feb 2005 10:20:03 +0100 writes:Pavel> this is a question, how can i specify the random part Pavel> in the GLMM-call (of the lme4 library) for compound Pavel> matrices just in the the same way as they defined in Pavel> the lme-Call (of the nlme library). ``twice in such a short paragraph -- yikes !!'' ... I'm getting convulsive... There is NO lme4 library nor an nlme one ! There's the lme4 *PACKAGE* and the nlme *PACKAGE* -- please -- (If the nlme package is built, it will rely on a nlme.so or nlme.dll (or nlme.dylib ...) *library* of compiled C code, and if packages are installed, they are installed into a library of packages; typically into one of the libraries in .libPaths() ) whooh.... Martin
Martin Maechler wrote:>>>>>>"Pavel" == Pavel Khomski <pkhomski at wiwi.uni-bielefeld.de> >>>>>> on Tue, 08 Feb 2005 10:20:03 +0100 writes: > > > > Pavel> this is a question, how can i specify the random part > Pavel> in the GLMM-call (of the lme4 library) for compound > Pavel> matrices just in the the same way as they defined in > Pavel> the lme-Call (of the nlme library).The GLMM function in the lme4 package allows you to specify crossed random effects within the random argument without the need for the pdBlocked and pdIdent constructions. Simply ensure that your grouping factors are defined in such a way that each distinct group has a different level in the grouping factor (this is usually not a problem for crossed grouping factors but can be a problem with nested factors) and list them. For example random = list(rows = ~ 1, columns = ~1)