Message/Author 

Shuwen Tang posted on Friday, November 02, 2012  3:08 pm



I want to examine a twolevel model with random slopes. Usually I just use the "S  y on X" statement in the within model. But this time I want to use the withinpart of X as the predictor. Instead of groupmeancentering X, I would like to use the latent variable approach. I tried the following syntax: %WITHIN% FXw by x @1; x@0; S Y ON FXw ; %BETWEEN% FXb by x@1; x@0; S Y on T; I got the error message saying that "THE ESTIMATED WITHIN COVARIANCE MATRIX COULD NOT BE INVERTED." Is there anything fundamentally wrong with this model? I appreciate your thoughts and input! 


See the third part of Example 9.2 where the input for this is shown. 

Shuwen Tang posted on Friday, November 02, 2012  9:00 pm



Thanks, Linda. In the example 9.2, I can only get an overall interaction estimation. What we want to see is to separate the interaction term into between and within parts. Do you have any ideas to get these using the latent variable approach, instead of groupmeancentering X? 

Shuwen Tang posted on Tuesday, November 06, 2012  4:12 pm



Or, how to deal with the error message saying that "THE ESTIMATED WITHIN COVARIANCE MATRIX COULD NOT BE INVERTED." Is there anything fundamentally wrong with the model I mentioned above? Thanks. 


Regarding using only the within part of the latent variable decomposition as a covariate in the random slope, this is not possible. Regarding the error message, please send the output and your license number to support@statmodel.com. 

Shuwen Tang posted on Tuesday, November 06, 2012  6:22 pm



why it is not possible? Example 9.10 shows a model in which a within latent variable is used as a covariate in the random slope. How is our model different from that example, except that we only have one indicator for the latent factor? 


Please send the full output and your license number to support@statmodel.com. 


Try fixing x at 0.0001 on both levels. x@0.0001; 

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