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Multilevel Data/Complex Sample
posted on Saturday, September 30, 2017 - 7:28 am
I am wondering if it is possible to estimate an intercepts-and-slopes-as-outcomes model with latent variables.
I have tried the following with a sample of 3,746 level 1 and 126 level 2 units:
lf02420, lf02430, lf02470
lf02440, lf02460, lf02500
between = sozibi;
IDVariable is ID;
Missing = Blank;
Analysis: Type=twolevel random;
Estimator = ml;
Algorithm = Integration;
PFSMw by lf02420*, lf02430, lf02470;
PFAMw by lf02440*, lf02460, lf02500;
beta1 | comm on PFSMw;
beta1 | comm on PFAMw;
PFSMb by lf02420*, lf02430, lf02470;
PFAMb by lf02440*, lf02460, lf02500;
comm on PFSMb;
comm on PFAMb;
beta1 comm on sozibi;
comm with beta1;
Unfortunately I always receive error messages like this:
"THE ESTIMATED BETWEEN COVARIANCE MATRIX COULD NOT BE INVERTED."
I have no clue what the problem may be. Did I misspecify something? Or is it impossible to estimate such a model with latent variables in general?
Bengt O. Muthen
posted on Sunday, October 01, 2017 - 12:47 pm
Look for close to zero between-level variances. Perhaps some slopes are not random.
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