[R-sig-ME] Nested Mixed Models in lme4
Marco Chiarandini
marco at imada.sdu.dk
Fri Nov 9 17:41:34 CET 2007
Dear Prof. Bates,
>> I am trying to use the function lmer from lme4 to
>> analyse the following nested factorial design.
>
>> I have three treatment factors (neighborhood,
>> initial, k);
>> I have three group factors crossing (size, dens,
>> inst).
>
> Did you mean to write (size, dens, type) there?
>
> Also, by "factor" do you mean that you regard all of these variables
> as categorical? If so, you should check the form of the size variable
> in the data frame. It is being stored as a numeric variable, not as a
> factor. If you want to interpret this variable as a categorical
> factor you should convert it to a factor or, as seems likely in this
> case, an ordered factor. (See ?factor and ?ordered)
yes, thank you a lot! All your corrections are
appropriate! inst should have been type and all
variables should have been categorical. My mistake.
Also: as you correctly pointed out, the data are
from a computer experiment and perfectly balanced,
and by group factors I meant blocking factors.
Your very clear explanation solved my concerns
about the nesting! Thanks!
I've also redone the comparison with SAS and now
results correspond.
The reason was mainly that I needed a quite
different formula:
lmer(err~initial*neighborhood + initial*k +
initial*type + initial*size + initial*dens +
neighborhood*k + neighborhood*type +
neighborhood*size + neighborhood*dens + k*type +
k*size + k*dens + type*size + type*dens +
size*dens + initial*neighborhood*k +
(1|inst),data=Case3)
True also that we were using lsmeans in SAS that
you discourage.
To me it would remain only to understand how I
could obtain the results in a cell means format
like those in SAS. But this seems to be a problem
also in lm and hence I must probably study better
how things work to find the way. Trying something
of the kind:
fmm1 <-
lmer(err~-1+ordered(size)+dens+type+(k+initial+neighborhood)^3+(1|inst),data=Case3)
does not seem to help much.
I left all the analysis I did, code + results,
(SAS and R) at:
http://www.imada.sdu.dk/~marco/Mixed/
Thank you a lot very much for the help!
Best regards,
Marco
--
Marco Chiarandini
http://www.imada.sdu.dk/~marco
Department of Mathematics Email:
marco at imada.sdu.dk
and Computer Science, Phone: +45 6550 4031
University of Southern Denmark Fax: +45
6593 2691
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