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OpenMx Forum.R [6] | 4.58 KB |
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Hi,
I am currently trying to fit the following model model: (picture, code and outcome attached)
I have data for 5 waves (2012-2016) on 4 observed Variables (-> x1_12, x2_12, ..., x4_16) that form a latent factor (= 5 CFAs for 5 years). (latent factor Naming: f12, f13, ..., f16)
The observed Variables have a range from 1-3, so I treated them as ordinal Variables.
I would like to fit a LGCM to those Factors.
I also have another factor (fy) measured by 3 indicators (y1, y2, y3), this factor should predict intercept and slope of the LGCM.
Those Indicators have a range from 1-5, so I treated them also as ordinal Variables.
The model does converge (with good fit, RMSEA = 0.03), however, the estimated slope variance is negative. Can someone tell me where I misspecified my model?
I fixed all unique factor variances to 1 and their covariance to 0. Would it be better to just fix those of the first measurement occasion? Should I allow any covariances?
Also, should I fix the intercept-slope covariance to 0? I have no specific theory about it.
Thanks in advance,
Maximilian