Hi, Iuri:
If you've got an 8086 AND a huge data set, compute time might be a
problem with 'lmer'. However, if you a reasonably modern computer and
only a a few thousand observations, 'lmer' should complete almost in the
blink of an eye -- or at least in less time than it would talk for a cup
of coffee.
Spencer
Doran, Harold wrote:
> This will (should) be a piece of cake for lmer. But, I don't speak SPSS.
> Can you write your model out as a linear model and give a brief
> description of the data and your problem?
>
> In addition to what Spencer noted as help below, you should also check
> out the vignette in the mlmRev package. This will give you many
> examples.
>
> vignette('MlmSoftRev')
>
>
>
>
>
> ________________________________
>
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf
> Of Iuri Gavronski
> Sent: Thursday, August 17, 2006 11:16 AM
> To: Doran, Harold
> Subject: Re: [R] Variance Components in R
>
>
> 9500 records. It didn`t run in SPSS or SAS on Windows machines,
> so I am trying to convert the SPSS script to R to run in a RISC station
> at the university.
>
>
> On 8/17/06, Doran, Harold <[EMAIL PROTECTED]> wrote:
>
> 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.
> >
>
>
>
>
> [[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.
>
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