Hey all you smart people! I am currently doing some research and encountered this issue in one my SEM-analysis. The full SEM model has a very high explained variance (Squared Multiple Correlations) for the explained latent variable.

Here is the full SEM model: http://1drv.ms/1oPm41w
Here is the output: http://1drv.ms/1oPlUXG

The model fit is not exactly great hence I wonder what possible explainations that could be for the high explained variance. My current idea is that some of the latent indicators have cross loading on the indicators but otherwise I am stumped! Hope someone can offer some clarify for a beginner in SEM-modelling.

Thanks!

I am currently doing some research and encountered this issue in one my SEM-analysis. The full SEM model has a very high explained variance (Squared Multiple Correlations) for the explained latent variable.

Here is the full SEM model:

The output is here: (pdf).

The model fit is not exactly great, hence I wonder what possible explanation there could be for the high explained variance. My current idea is that some of the latent indicators have cross loadings on the indicators, but otherwise I am stumped!