Missing Data

owis — Sat, 13 Aug 2011 04:47:20 GMT

Hi Everyone,

i am new in this forum and i hope finding my answer here.

i am working on missing data treatment; i used "proc mi" to do imputation of missing data.

i used this code:

proc mi data = time1 nimpute = 5 seed = 4321567 out=itime1;

run;

But i got these warning messages:

(WARNING: All observed values are identical for variable surveyId. This variable will be excluded from

the analysis.

WARNING: A covariance matrix computed in the EM process is singular. The linearly dependent variables

for the observed data are excluded from the likelihood function. This may result in an

unexpected change in the likelihood between iterations prior to the final convergence.

WARNING: The EM algorithm (MLE) fails to converge after 200 iterations. You can increase the number

of iterations (MAXITER= option) or increase the value of the convergence criterion

(CONVERGE= option).

WARNING: The EM algorithm (posterior mode) fails to converge after 200 iterations. You can increase

the number of iterations (MAXITER= option) or increase the value of the convergence

criterion (CONVERGE= option).

WARNING: The EM algorithm (posterior mode) fails to converge after 200 iterations. You can increase

the number of iterations (MAXITER= option) or increase the value of the convergence

criterion (CONVERGE= option).

WARNING: The posterior covariance matrix is singular. Imputed values for some variables may be fixed.)

I dont know where is the problem. so could anyone help me in that.

Thanks

Owis

art297 — Sat, 13 Aug 2011 16:02:55 GMT

If you can post your time1 dataset it would help others to see why you got all of the warnings.

topic Missing Data in Statistical Procedures