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| Latent Intercepts-and-Slopes-as-Outco... |
 
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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:
Usevariables are
lf02420, lf02430, lf02470
lf02440, lf02460, lf02500
comm sozibi;
between = sozibi;
Cluster=idschool;
IDVariable is ID;
Missing = Blank;
Analysis: Type=twolevel random;
Processors=4;
Estimator = ml;
Algorithm = Integration;
Integration=montecarlo;
model:
%within%
PFSMw by lf02420*, lf02430, lf02470;
PFAMw by lf02440*, lf02460, lf02500;
PFSMw@1;
PFAMw@1;
beta1 | comm on PFSMw;
beta1 | comm on PFAMw;
%between%
PFSMb by lf02420*, lf02430, lf02470;
PFAMb by lf02440*, lf02460, lf02500;
PFSMb@1;
PFAMb@1;
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? |
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| Look for close to zero between-level variances. Perhaps some slopes are not random. |
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