Date: Wed, 3 Feb 2010 10:47:24 -0600
Reply-To: Robin R High <rhigh@UNMC.EDU>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Robin R High <rhigh@UNMC.EDU>
Subject: Re: PROC MIXED for non-normal data
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Yes the RANDOM in GLIMMIX looks much like the REPEATED in MIXED, though
you need to specify residual or Rside, something like
REPEATED time / subject=id type=ar(1) R Rcorr;
in GLIMMIX becomes:
RANDOM time / subject=id type=ar(1) v vcorr residual; * or add Rside;
02/03/2010 10:27 AM
Re: PROC MIXED for non-normal data
"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
On Feb 3, 4:51 pm, rh...@UNMC.EDU (Robin R High) wrote:
> Every dataset has its own issues to work around, but first want to make
> sure you are basing your comments about non-normality based on a
> analysis (such as described in Chapter 10 of "SAS for Mixed Models", 2nd
> ed.) and not on how the original data look. GLIMMIX has some
> distribution alternatives that might make an improvement over the normal
> without computing a transformation,which works much like PROC MIXED.
> Robin High
> Christoff <14353...@SUN.AC.ZA>
> 02/03/2010 08:29 AM
> PROC MIXED for non-normal data
> Sent by:
> "SAS(r) Discussion" <SA...@LISTSERV.UGA.EDU>
> Hello all,
> Can one use PROC MIXED on non-normally distributed data? I have heard
> it is robust to the assumptions. If so, are there any references in
> literature that support this?
> My dataset consist of body temperatures measured hourly across +-10
> sequential days during summer, autumn, winter and spring. I used
> different study subjects (lizards) during each season, and
> experimental day therefore is the repeated measure.
> Both the number of experimental days and the number of lizards used
> vary among seasons resulting in an unbalanced design.
> PROC MIXED is the only model I know of that can handle unbalanced
> repeated measures data. Does anyone know of non-parametric
> I have tried various transformations yet could not improve normality.
> Kind regards
Yes indeed the residual distributions are non-normal in most of the
It seems as though Proc GLIMMIX might do the trick, just a quick
question..I have quickly had a look at PROC GLIMMIX and noticed it has
no repeated statement. Does one simply include the repeated measure in
the RANDOM statement?