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Posted 02-27-2018 01:46 PM
(3580 views)

I am having trouble generating pooled effect estimates for an interaction between two categorical variables, using multiple linear regression with robust variance estimation and stabilized inverse probability of treatment weights - essentially a 'multiple informant' model. The code I'm working with is:

```
Proc genmod data=data plots=(dfbetacs);
class studyid predict_1 (ref='0');
model z_bw=predict_1*time race*time bmi*time age*time educat*time smoke*time/noint dist=normal link=identity id=studyid;
repeated subject=studyid/type=ind ecovb;
weight &weight;
by _imputation_;
ods output GEEEmpPEst=emp_est GEERCov=emp_covb
parmInfo=pinfo;
run;
Proc mianalyze parms(classvar=level)=emp_est covb = emp_covb parminfo=gmpinfo mult;
class predict_1*time;
modeleffects predict_1*time;
run;
```

Predict_1 is a 3 level categorical variables (i.e., 1st, 2nd, 3rd tertile), time is a 2 level categorical variable. My model works fine but I'm unable to generate the pooled estimate for predict_1*time at each of the 6 potential levels. However, I am receiving an error message that I've been unable to correct in that SAS doesn't appear to be recognizing the "predict_1*time" as an effect/Parm name:

"ERROR 22-322: Syntax error, expecting one of the following: a name, ;, -."

"ERROR 200-322: The symbol is not recognized and will be ignored."

Any ideas? Please!

1 ACCEPTED SOLUTION

Accepted Solutions

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Try this:

```
Proc mianalyze parms(classvar=level)=emp_est;
class predict_1;
modeleffects predict_1*time;
run;
```

You won't be able to use the MULT option since you have a CLASS variable. This also means you do not need the COVB= option either.

4 REPLIES 4

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Use

**class predict_1 time;**

no asterisk.

PG

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Try this:

```
Proc mianalyze parms(classvar=level)=emp_est;
class predict_1;
modeleffects predict_1*time;
run;
```

You won't be able to use the MULT option since you have a CLASS variable. This also means you do not need the COVB= option either.

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