Corr>1 between second and first-order... PreviousNext
Mplus Discussion > Confirmatory Factor Analysis >
 Carmen Borrat-Besson posted on Thursday, August 15, 2013 - 8:06 am

I'm running the following second-order model:

CNTRL BY u1 u2 c3;
PLSR BY u7 u8 u9;
SLFRLZTN BY u10 u11 u12 ;
PLSR (1)

My indicators are categorical and I'm using the WLSMV estimator.

However, I'm getting a non positive definite covariance matrix.

I think that this is due to the fact that CASP, the second-order latent variable, is strongly related to SLFRLTZN, one of the first order latent variable. The estimated correlation is a bit higher than 1.

Moreover, the completely standardized factor loading for SLFRLZTN is a bit higher than 1 (STDXY loading=1.026) and it's residual variance is very small, negative and non-significant (residual=-.052, p=.999).

I read on the forum that I could fix the residual variance to 0. Is this what you would advice in my case?

Theoretically, would then this mean that CASP = SLFRLZTN ? In other words, that my second order latent variable is redundant?

 Linda K. Muthen posted on Thursday, August 15, 2013 - 2:41 pm
When factors correlate one or greater, it means that they are not statistically distinguishable. You might try an EFA on your first-order factors or look at modification indices for cross-loadings to see if the problem is with the specification of the first-order factors.
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