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Corr>1 between second and first-order... |
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Hi, I'm running the following second-order model: CNTRL BY u1 u2 c3; PLSR BY u7 u8 u9; SLFRLZTN BY u10 u11 u12 ; CASP BY CNTRL PLSR (1) SLFRLZTN (2); [CNTRL@0 PLSR@0 SLFRLZTN@0]; 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? Thanks! |
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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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