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Mplus Discussion > Growth Modeling of Longitudinal Data >
Message/Author
 Sarah Lowe posted on Tuesday, June 27, 2017 - 6:25 pm
Hello!

I am working with an integrated dataset and am trying to run a LCGA with t-scores. Unfortunately, I am getting the following error:

The number of fixed time scores is not sufficient for model identification in the following growth process: I S Q

For your reference, here is my model:

******

USEVARIABLES ARE v1 v2 v3 v4
TIME1 TIME2 TIME3 TIME4;
TSCORES = TIME1 TIME2 TIME3 TIME4;
CLASSES = C(1);


ANALYSIS: TYPE = RANDOM MIXTURE;
ESTIMATOR IS MLR;
STARTS = 500 20;
STITERATIONS = 20;

MODEL:


%OVERALL%

i s q | v1 v2 v3 v4 @
TIME1 TIME2 TIME3 TIME4;

i s q WITH i s q; i; s; q;
v1; v2; v3; v4;

%C#1%
[i s q];
i s q WITH i s q;
i; s; q;
v1; v2; v3; v4;

****

I am wondering if this has to do with the large variability in timing within each t-score, as well as the extent of missing data? Here are the ranges for the t-scores:

Time 1: 0 to 61 days (Median = 18)
Time 2: 62 to 183 days (Median = 110)
Time 3: 184 to 301 days (Median = 207)
Time 4: 305 to 487 days (Median = 376)


The between-time covariance coverage ranges from 0.126 to 0.557

Any insight you have on this matter would be greatly appreciated!

Thanks so much,
Sarah
 Linda K. Muthen posted on Wednesday, June 28, 2017 - 6:14 am
Try the following:

i s q | v1 - v4 at TIME1 - TIME4;
 Sarah Lowe posted on Wednesday, June 28, 2017 - 5:27 pm
Thanks for the help - changing the @ to AT worked!
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