Individually time-varying measurements PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
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 Douglas Gunzler posted on Tuesday, January 08, 2013 - 4:46 pm
In a study with a large dataset we are setting time for each patient's baseline measurement to zero and then each follow-up time is in months since the baseline measurement. There are 8 potential time points with lots of individual variation on number of time points and time of follow-up. The whole study is four years. Is this the best way to specify the LGC model or would I be better off with different model assumptions about time:

TSCORES = months2-months8
;
Analysis:
TYPE = RANDOM MISSING;
ESTIMATOR = ML;
ALGORITHM=INTEGRATION;
MCONVERGENCE = .001;
Model:
i | d1@0;
i s | d2-d8 AT months2-months8;
 Bengt O. Muthen posted on Tuesday, January 08, 2013 - 9:09 pm
I think you should simply have

i s | d1-d8 AT months0-months8;

where everyone has months0=0.
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