Iuri: The lmer function is optimal for large data with crossed random effects. How large are your data?
> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Iuri Gavronski > Sent: Thursday, August 17, 2006 11:08 AM > To: Spencer Graves > Cc: r-help@stat.math.ethz.ch > Subject: Re: [R] Variance Components in R > > Thank you for your reply. > VARCOMP is available at SPSS advanced models, I'm not sure > for how long it exists... I only work with SPSS for the last > 4 years... > My model only has crossed random effects, what perhaps would > drive me to lmer(). > However, as I have unbalanced data (why it is normally called > 'unbalanced design'? the data was not intended to be > unbalanced, only I could not get responses for all cells...), > I'm afraid that REML would take too much CPU, memory and time > to execute, and MINQUE would be faster and provide similar > variance estimates (please, correct me if I'm wrong on that point). > I only found MINQUE on the maanova package, but as my study > is very far from genetics, I'm not sure I can use this package. > Any comment would be appreciated. > Iuri > > On 8/16/06, Spencer Graves <[EMAIL PROTECTED]> wrote: > > > > I used SPSS over 25 years ago, but I don't recall > ever fitting a > > variance components model with it. Are all your random > effects nested? > > If they were, I would recommend you use 'lme' in the 'nlme' package. > > However, if you have crossed random effects, I suggest you > try 'lmer' > > associated with the 'lme4' package. > > > > For 'lmer', documentation is available in Douglas > Bates. Fitting > > linear mixed models in R. /R News/, 5(1):27-30, May 2005 > > (www.r-project.org -> newsletter). I also recommend you try the > > vignette available with the 'mlmRev' package (see, e.g., > > http://finzi.psych.upenn.edu/R/Rhelp02a/archive/81375.html). > > > > Excellent documentation for both 'lme' (and indirectly for > > 'lmer') is available in Pinheiro and Bates (2000) > Mixed-Effects Models > > in S and S-Plus (Springer). I have personally recommended > this book > > so many times on this listserve that I just now got 234 hits for > > RSiteSearch("graves pinheiro"). Please don't hesitate to pass this > > recommendation to your university library. This book is > the primary > > documentation for the 'nlme' package, which is part of the > standard R > > distribution. A subdirectory "~library\nlme\scripts" of your R > > installation includes files named "ch01.R", "ch02.R", ..., > "ch06.R", > > "ch08.R", containing the R scripts described in the book. These R > > script files make it much easier and more enjoyable to study that > > book, because they make it much easier to try the commands > described > > in the book, one line at a time, testing modifications to check you > > comprehension, etc. In addition to avoiding problems with > > typographical errors, it also automatically overcomes a few > minor but > > substantive changes in the notation between S-Plus and R. > > > > Also, the "MINQUE" method has been obsolete for over > 25 years. > > I recommend you use method = "REML" except for when you want to > > compare two nested models with different fixed effects; in > that case, > > you should use method = "ML", as explained in Pinheiro and > Bates (2000). > > > > Hope this helps. > > Spencer Graves > > > > Iuri Gavronski wrote: > > > Hi, > > > > > > I'm trying to fit a model using variance components in R, but if > > > very new on it, so I'm asking for your help. > > > > > > I have imported the SPSS database onto R, but I don't know how to > > > convert the commands... the SPSS commands I'm trying to > convert are: > > > VARCOMP > > > RATING BY CHAIN SECTOR RESP ASPECT ITEM > > > /RANDOM = CHAIN SECTOR RESP ASPECT ITEM > > > /METHOD = MINQUE (1) > > > /DESIGN = CHAIN SECTOR RESP ASPECT ITEM > > > SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP > > > CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM > > > SECTOR*RESP*ASPECT SECTOR*RESP*ITEM > CHAIN*RESP*ASPECT > > > /INTERCEPT = INCLUDE. > > > > > > VARCOMP > > > RATING BY CHAIN SECTOR RESP ASPECT ITEM > > > /RANDOM = CHAIN SECTOR RESP ASPECT ITEM > > > /METHOD = REML > > > /DESIGN = CHAIN SECTOR RESP ASPECT ITEM > > > SECTOR*RESP SECTOR*ASPECT SECTOR*ITEM CHAIN*RESP > > > CHAIN*ASPECT CHAIN*ITEM RESP*ASPECT RESP*ITEM > > > SECTOR*RESP*ASPECT SECTOR*RESP*ITEM > CHAIN*RESP*ASPECT > > > /INTERCEPT = INCLUDE. > > > > > > Thank you for your help. > > > > > > Best regards, > > > > > > Iuri. > > > > > > _______________________________________ > > > Iuri Gavronski - [EMAIL PROTECTED] > > > doutorando > > > UFRGS/PPGA/NITEC - www.ppga.ufrgs.br Brazil > > > > > > ______________________________________________ > > > 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. > > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > ______________________________________________ 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.