Youyou Tao posted on Tuesday, June 06, 2017 - 3:36 pm
I have a dataset with data from 7 states in the US. So I am using state to cluster my data (cluster = state) and used type= complex in the analysis part.
However, I always get this message: "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 MAY BE DUE TO THE STARTING VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE CONDITION NUMBER IS -0.654D-16. PROBLEM INVOLVING THE FOLLOWING PARAMETER: Parameter 7, [ B_4YI ]
THIS IS MOST LIKELY DUE TO HAVING MORE PARAMETERS THAN THE NUMBER OF CLUSTERS MINUS THE NUMBER OF STRATA WITH MORE THAN ONE CLUSTER."
So, my first question is whether I can trust my result if I get this message.
After I removed the type= complex, this error message disappeared and my model runs fine.
So, my second question is whether I should code different state into binary variables and run the state effect as co-variance instead using the cluster?