Thanks for your help.


Rickie Domangue
Dept. of Math & Stats
James Madison University



--On Monday, May 20, 2002 8:48 AM -0400 "E. Jacquelin Dietz" 
<[EMAIL PROTECTED]> wrote:

> Here are comments from two of my colleagues at NC State in response to
> Rickie Domangue's message about proc mixed (see below).
>
> Jackie Dietz
>
>
> From Joy Smith:
> -------------------------------
> There are some more examples for proc mixed on the SAS web site.
>
> Here is a link to the statistical samples:
> http://ftp.sas.com/techsup/download/stat/
>
> There also some in the Proc Mixed section of the SAS OnLineDoc.
> OnlineDoc is
> available on the SAS web site at:
> http://v8doc.sas.com/sod_register.html
> -------------------------------
>
>
> From Dave Dickey:
> -------------------------------
> I believe the reason you do not see time*block in a random statement
> is that this would imply an additive random component that changes
> each time a new (block,time) level is encountered.  If you treat
> this as a repeated measures type of situation, then a term like
> time(block*A) would seem to be sufficient to model this kind of
> effect.
>
> The random statement sets up some matrices of (often) dummy variables
> and you could think of the repeated statement in a similar vein. You
> essentially want to avoid specifying two or more effects whose columns
> span the same space (your dependency question).
>
> In fact the effect of the repeated statement can often be reproduced by
> a careful invocation of a corresponding random statement.  In the
> program
> below I generate and analyze data from a split plot with repeated
> measures on the whole plots. Notice that I have used the RANDOM
> statement rather than the repeated statement to get my repeated
> measures analysis on the whole plots.  My model is
>   Y(i,j,k,t) = mu + Block(i)+ A(j) + D(i,j) + w(i,j,,t)
>              + B(k) + AB(j,k) + e(i,j,k,t)
> As it stands, the whole plot error is D(i,j)+w(i,j,t)
> and I have let the w(i,j,t) have an autoregressive order 1 structure.
> You could also have a model without the D, or of course fit both
> and test D (I would recommend not using the default Wald tests -
> do a likelihood ratio calculation)
>    If you follow this program more or less, you should not have
> any dependency problems.
> D. A. Dickey
> NCSU
>
> ===============PROGRAM ===================================
> data a; et=normal(1827655)/sqrt(1-.5*.5);
>   do block = 1 to 4;  BEFF=8*normal(9876655);
>      do A = 1 to 2;
>           EA = 2*normal(1827655);
>           do time=1 to 5;
>           ET = .5*et + normal(1827655);
>           Ypart = BEFF + 2*A +EA + ET;
>         do B = 1 to 3;
>           Y=Ypart - 3*B +A*B + normal(1827655);
>         output; end;end; end; end;
> proc glm; class a b block;
> model Y = block a block*a b a*b;
> proc mixed; class block a b time;
>   model Y = a|b;
> random block  a*block;
> random time(a*block)/type=ar(1);
> repeated time/subject=a*b*block
>     /*type=ar(1)*/;
>    * This would fit an AR(1) structure within the split plots ;
> run;
> -------------------------------
>
>> Rickie Domangue wrote:
>>
>> > Can anyone help or provide resources for
>> > help with the following mixed model analysis questions
>> > in SAS proc mixed?
>> >
>> > 1.  Understanding when specifications for the random
>> >     and repeated statements for repeated measures designs
>> >     result in confounding of certain variance components.
>> >     SAS System for Mixed Models provides a couple of examples.
>> >     Are there other places that I could look?  In particular,
>> >     I'm looking for the situation when the design is a split
>> >     plot with whole plots blocked and repeated measures taken
>> >     on the whole plots.
>> >
>> > 2.  In a split plot design, with levels of factor A assigned
>> >     to whole plots, with whole plots blocked, and repeated
>> >     measures over time on the whole plots, including or not
>> >     including the block x time interaction in the
>> >     random statement. In most examples of split plot design analysis
>> >     in proc mixed that I see, this term is omitted.
>> >
>> > Thanks for any help.
>> >
>> > Rickie Domangue
>> > Dept. of Math & Stats
>> > James Madison University
>> >
>> > email:  [EMAIL PROTECTED]
>> > phone:  540-896-4232
>> >
>> > --
>> > Domangue, Rickie James
>> > [EMAIL PROTECTED]
>
> --
> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>   E. Jacquelin Dietz                       (919) 515-1929  (phone)
>   Department of Statistics, Box 8203       (919) 515-1169  (FAX)
>   North Carolina State University
>   Raleigh, NC  27695-8203   USA            [EMAIL PROTECTED]
>
>   Street address for FedEx:
>   Room 210E Patterson Hall, 2501 Founders Drive
> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
> .
> .
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-- 
Domangue, Rickie James
[EMAIL PROTECTED]
.
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