Date:         Wed, 3 Feb 2010 09:56:05 -0500
Reply-To:     Peter Flom <peterflomconsulting@mindspring.com>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Peter Flom <peterflomconsulting@MINDSPRING.COM>
Subject:      Re: PROC MIXED for non-normal data
Comments: To: Christoff <14353075@SUN.AC.ZA>
Content-Type: text/plain; charset=UTF-8

Christoff <14353075@SUN.AC.ZA> wrote
>
>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
>alternatives?
>I have tried various transformations yet could not improve normality.


It's not clear from this what is non-normal, but what about PROC GLIMMIX?

Peter

Peter L. Flom, PhD
Statistical Consultant
Website: http://www DOT statisticalanalysisconsulting DOT com/
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