

Correlation between intercept and slope 

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When there is high (almost perfect) correlation between intercept and slope in growith curve model, the model fails to run or gives improper solution. When I ran the model with random options and analysis it failed to run with saying "nonpositive defninite estimated correlation matrix". I guess this is the natural reaction of mplus because intercept or slope factor has negative or 0 residual variance if the correlation between them is close to 1(or 1). Is there any remedy for this problem? 


Assuming that the random slope has a significant variance, you could try centering at another time point. 


I have a similar question. My slope and intercept are highly correlated (more than .80). So far I have done it so, that the loading of the variable at Time 1 is set to 0). However, when I center so that intercept is the last time point, the correlation is even higher. It would not be such a problem, but I am trying to examine whether individual differences in the slope and intercept predict differences in other variables. So...what would be the solution? Should I try to do growth mixture analysis? Thank you. 


I forgot to add...the problem is that when I include both the intercept and slope in the model, all the paths are nonsignificant. However, the paths from the intercept become significant when I fix the paths from the slope to be zero (and the other way around). 


Try centering at the average. If that does not help, please send your input, data, output, and license number to support@statmodel.com. 

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