Hello, I am running an SEM model with a single latent variable. The latent variable has three indicators that have intercorrelations of r= .55, .26, & .63. When I try to run the measurement model, I get the following error message.
WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IS NOT POSITIVE DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES. CHECK THE RESULTS SECTION FOR MORE INFORMATION. PROBLEM INVOLVING VARIABLE DASSS.
How should I interpret this error message? I do not see a problem with multicollinearity when I test for it in Stata (the condition index is less than 10). I see that I am getting a negative residual for the one variable listed as the problem variable. But I don't understand why this would be happening. Any guidance would be much appreciated!
I see. That is very surprising to me because these are all measures of anxiety. And when I run the structural model, the standardized paths for the three indicators are .55, .98, and .64. Is there any way to figure out why these measures are not making a good factor? Thank you for your help!!