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# proc mixed with imputated (multiple) data

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a week ago

Hello,

I have got a problem and wondering if someone can help me please. I am trying Proc Mixed with the random intercept: and getting a problem. I have done multiple imputation (so, there are 10, for example _imputation_ = 1 ...._imputation_ = 10). The proc mixed is as follows (variable names are just for example):

**proc** **sort** data = reg_fin_1 ;

by _imputation_ ID ;

**run**;

**proc** **mixed** data = reg_fin_1 noitprint PLOTS(MAXPOINTS= **20000000000**) ;

class ID ;

by _imputation_ ;

model Y = x1 x2 x3

/solution ddfm = bw residual ;

random intercept / subject = NEW_PIN type = un ;

ods output solutionF=mxparms3 ;

**run**;

**The problem is that I get the following message: **

Estimated G matrix is not positive definite.

The above message was for the following BY group: _imputation_=1

Estimated G matrix is not positive definite.

The above message was for the following BY group: _imputation_=2

......

.......

**However, I don't get this notice when I run proc mixed with the complete cases: I mean, excluded the missing values, hence no imputation, and unlike the multiple imputation I have one dataset. **

Thanks to all.

Rahid

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a week ago

Hello,

Thanks to everyone. This "error" has been solved: the problem was due to the organization the imputed data properly. Howeve, I have **another question**: First of all, this is a longitudinal/panel data. I have a random intercept model and the G matrix I am getting **shows (only) row one for the first ID**:

Estimated G Matrix

Row Effect NEW_PIN Col1

1 Intercept 10001 0.1448