Posted by
Ryan on
URL: http://spssx-discussion.165.s1.nabble.com/SPSS-Syntax-MIXED-Model-tp5713934p5713967.html
I believe Alex's parameterization is headed in the desired direction
of the OP. I might take issue with using a "UNR" structure instead of
a "UN" structure to start but I'll save my reasoning for another time.
Nevertheless, more needs to be done with respect to the fixed effects
component of the model to answer the original research question,
"...effect of each independent variables such as age, gender and
ethnicity on the decline of this blood test over time." In order to do
so, the FIXED statement needs to be modified as follows:
/FIXED = Gender Ethnicity Age Time_point Gender*Time_point
Ethnicity*Time_point Age*Time_point | SSTYPE(3)
Whether the OP wants to incorporate a REPEATED statement (which is
known as a "residual change model") versus a RANDOM statement with an
intercept and slope (which is known as a growth curve model) depends
on whether the OP is interested in estimating differences between
individual linear trajectories over time. If so, the
random-coefficient regression model (the model with the RANDOM
statement with an intercept and slope) is the way to go.
BTW, ignoring the fixed effects component for the moment, there is
absolutely nothing wrong with a combination of the RANDOM and REPEATED
statements posted originally by the OP. These statements combined in
the same model indicate that conditional upon the subject-specific
intercepts, there is residual correlation from observations obtained
by the same subject along with time-invariant residual variances. The
problem is that a random intercept coupled with an UNstructured
residual correlation matrix is inconsistent with what the OP
described. Furthermore, the fixed effects component did not include
Time_point or its interaction with the other variables, which are both
necessary in order to assess the effect of the independent variables
on the temporal linear change in the expected value of y.
Finally, no explanation was provided as to why the number of
measurements per subject varied between 2 and 15. I would be
interested in understanding why this is the case. This leads me to
wonder about various other aspects of the variable Time_point but I'll
refrain from going any further for now.
HTH,
Ryan
On Mon, Jul 2, 2012 at 2:13 PM, Alex Reutter <
[hidden email]> wrote:
> Model 11 will not estimate a random slope, as stated as desired in the
> original post, while Model 5 will. I think there can be good reasons for
> fitting the data either way, but you need to decide what you're trying to
> estimate.
>
> I also just realized that Time_point is your index for repeated measurements
> and not Age, and so would amend the random coefficients model to be:
>
> MIXED
> Blood_test_Value BY Gender Ethnicity WITH Age Time_point
> /FIXED = Gender Ethnicity Age Time_point | SSTYPE(3)
> /METHOD = REML
> /RANDOM INTERCEPT Time_point | SUBJECT(id) COVTYPE(UNR) .
>
> Alex
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