I want to regress a continuous predictor on a categorical variable (4 categories or three dummy coded predictors).
I have missing data on the dependent but obviously not on the IVs. The N = 368.
My purpose is to examine group differences and to use maximum likelihood to address missing data ( focusing specifically on one of the groups as the reference).
I have specified the variances in the model and it produces interpretable results. But I keep getting a non-positive definite message. THE MODEL ESTIMATION TERMINATED NORMALLY THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES MAY NOT BE TRUSTWORTHY FOR SOME PARAMETERS DUE TO A NON-POSITIVE DEFINITE FIRST-ORDER DERIVATIVE PRODUCT MATRIX.
This is a very simple model. The results make sense and my interest is in the resulting estimates. Do I need to address this error? If so, how can I improve the model to accommodate the error?