Hi Ryan
Thanks for this.
A test shows the two methods do indeed produce identical global fit
statistics. Where the coefficents are comparable they are the same, and
EMMEANS gives identical estimates.
About the only difference is that in the second model the numerator df for
some terms (those involving Y_indic) are 0.
Garry
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of R B
Sent: 09 May 2011 04:02
To:
[hidden email]
Subject: Re: Mixed model with multiple pre and post measures.
Garry,
The NOINT keyword is noted to eliminate a grand intercept from the
model. The grand intercept has been removed from the model because of
the multivariate parameterization:
/FIXED = y_indic
y_indic*group
y_indic*time
y_indic*group*time | NOINT
Notice that the main effects, group and time, along with the grand
intercept, are not included in the fixed effects equation above. This
allows for direct estimation of separate intercepts for each level of
the response variable and response specific "slopes" for group, time
and group-BY-time effects. An equivalent parameterization that
includes the grand intercept would be:
/FIXED = y_indic
group
time
y_indic*group
y_indic*time
group*time
y_indic*group*time
If my thinking is correct, the global fit statistics of each
parameterization should be identical. That is, you are essentially
fitting the same model in a different way. Use the TEST statements to
answer specific research questions.
Ryan
On Fri, May 6, 2011 at 10:10 AM, Garry Gelade
<
[hidden email]> wrote:
> Ryan
>
> Thanks for this. The doubly repeated design you are modelling is what I
> have.
> One question (which I suspect is to do with something else but I'm
curious)
> - why the NOINT on the FIXED subcommand?
>
> Garry
>
> -----Original Message-----
> From: R B [mailto:
[hidden email]]
> Sent: 06 May 2011 13:44
> To: Garry Gelade
> Cc:
[hidden email]
> Subject: Re: Mixed model with multiple pre and post measures.
>
> Garry,
>
> I don't have time to review this thread carefully, but it sounds like
> you may have two repeated measures variables. Let me direct you to a
> recent post which was focused on fitting a doubly repeated measures
> multivariate model using the MIXED procedure.
>
>
http://www.listserv.uga.edu/cgi-bin/wa?A2=ind1104&L=spssx-l&P=R23020>
> Hope this gives you some direction.
>
> Ryan
>
> On Fri, May 6, 2011 at 7:14 AM, Garry Gelade
> <
[hidden email]> wrote:
>> Thanks Gene for your kind assistance.
>>
>>
>>
>> The examples were helpful, but I am still unsure about your solution.
>>
>>
>>
>> The problem I am wrestling with is that
>>
>> /REPEATED=activityType | subject(idvar )
>>
>> only seems to reflect one part of the structure (activtyType within
> person)
>>
>>
>>
>> That would be fine with only one instance of activityType within person,
>> but there are multiple instances (activities) of the same activityType
>> within person as well. What I would really like to model is both the
>> activityType within person as you suggest, but also the activities within
>> activityType. i.e. activity WITHIN activityType WITHIN person.
>>
>>
>>
>> Or am I barking up the wrong tree?
>>
>>
>>
>> Anyway, as only one REPEATED statement is allowed, I've decided to
>> experiment with /RANDOM=INTERECPT|SUBJECT(idvar) and /REPEATED activity
>> |SUBJECT(idvar*activityType)
>>
>>
>>
>> ... and see where that gets me!
>>
>>
>>
>> As always, your thoughts are welcome.
>>
>>
>>
>>
>>
>> Regards
>>
>> Garry
>>
>>
>>
>> From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
>> Gene Maguin
>> Sent: 05 May 2011 15:27
>>
>> To:
[hidden email]
>> Subject: Re: Mixed model with multiple pre and post measures.
>>
>>
>>
>> Garry,
>>
>>
>>
>> Perhaps you didn't know but the Mixed section of the syntax reference has
> a
>> number of example analysis setup. Adapting example 9, i would use this
>> syntax.
>>
>>
>>
>> MIXED Score BY Gender activityType
>>
>> /FIXED=Gender activityType Gender*activityType | SSTYPE(3)
>>
>> /METHOD=REML/PRINT= G SOLUTION TESTCOV
>>
>> /REPEATED=activityType | subject(idvar) covtype (see list).
>>
>>
>>
>> Although you may prefer a repeated measures model. you could also
> structure
>> this as a two time point growth model model. To do so would require that
>> activity type be a numeric var. Assuming that,
>>
>>
>>
>> MIXED Score with Gender activityType
>>
>> /FIXED=Gender activityType Gender*activityType | SSTYPE(3)
>>
>> /METHOD=REML/PRINT= G SOLUTION TESTCOV
>>
>> /RANDOM=INTERCEPT activityType | subject(idvar) covtype (un).
>>
>>
>>
>> Ryan Black has offered repeated measures models with random intercepts.
If
>> you search for his posts, you will find examples of these.
>>
>>
>>
>> Gene Maguin
>>
>>
>>
>>
>>
>> ________________________________
>>
>> From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of
>> Garry Gelade
>> Sent: Thursday, May 05, 2011 7:42 AM
>> To:
[hidden email]
>> Subject: Mixed model with multiple pre and post measures.
>>
>> Dear Listers,
>>
>>
>>
>> Advice needed on MIXED.
>>
>>
>>
>> I have subjects whose brains were measured doing several different
>> activities. The activities are categorized into types (eg Stress/Rest,
> Eyes
>> Open/Closed, and I am interested in the effect of activity type (rather
> tha
>> activity) on the scores.
>>
>>
>>
>> The logical structure of the data is:
>>
>>
>>
>> Person Gender Activity activityType Score
>>
>> 1 M 1 A 100
>>
>> 1 M 2 A 101
>>
>> 1 M 3 B 102
>>
>> 1 M 4 B 103
>>
>> 2 F 1 A 200
>>
>> 2 F 2 A 201
>>
>> 2 F 3 B 202
>>
>> 2 F 4 B 203
>>
>> 3 M 1 A 100
>>
>> 3 M 2 A 101
>>
>> ....
>>
>>
>>
>>
>>
>> I'm thinking something like
>>
>>
>>
>> MIXED Score BY Gender activityType
>>
>> /FIXED=Gender activityType Gender*activityType | SSTYPE(3)
>>
>> /METHOD=REML /PRINT= G SOLUTION TESTCOV
>>
>> /REPEATED= ?????
>>
>>
>>
>> Can anyone suggest appropriate syntax for the /REPEATED line(s)?
>>
>>
>>
>> Thanks for any thoughts.
>>
>>
>>
>>
>>
>> Garry Gelade
>>
>>
>>
>>
>>
>>
>
>
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