PROC MIANALYZE and getting odds ratios

[Thuva]

Hello,

I've tried to use the following link to run logistic regression on my imputed data to obtain the final odds ratios and 95%CIs:

 https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_mianalyze_s...

I am interested in a model with 2 categorical variables (location and treatment). This is my code:

Step 1:
proc logistic data=outmi;
class satis_analg location treatment (ref='Morphine');
model satis_analg(event='Yes')=treatment location/ covb;
by _Imputation_;
ods output ParameterEstimates=lgsparms
CovB=lgscovb;
run;

When I run this step, I get the following NOTES. Also, I have tried this entire process with adding the outcome 'satis_analg' to the CLASS statement, it still doesn't fix the issue. 

NOTE: Option EVENT= is ignored since LINK=CLOGIT.
NOTE: PROC LOGISTIC is fitting the cumulative logit model. The probabilities modeled are summed
over the responses having the lower Ordered Values in the Response Profile table. Use the
response variable option DESCENDING if you want to reverse the assignment of Ordered Values
to the response levels.
NOTE: Convergence criterion (GCONV=1E-8) satisfied.

STEP 2: 
proc mianalyze parms=lgsparms
covb(effectvar=stacking)=lgscovb;
modeleffects treatment location;
run;

When I run this step I get the following ERROR:

ERROR: Variable treatment is not in the COVB= data set

This is what my lgsparm dataset looks like. I'm not sure why there are 2 intercepts:

proc print data=lgsparms (obs=10); run;

Obs	_Imputation_	Variable	ClassVal0	DF	Estimate	StdErr	WaldChiSq	ProbChiSq	_ESTTYPE_
1	1	Intercept	1	1	-6.3562	1.0228	38.6215	<.0001	MLE
2	1	Intercept	No	1	-2.1939	0.2511	76.3405	<.0001	MLE
3	1	treatment	Hydromorphone	1	0.0155	0.1458	0.0113	0.9155	MLE
4	1	location	JH	1	-0.5374	0.4260	1.5915	0.2071	MLE
5	1	location	MUMC	1	0.0318	0.3537	0.0081	0.9284	MLE
6	2	Intercept	.95	1	-6.3562	1.0228	38.6215	<.0001	MLE
7	2	Intercept	No	1	-2.1939	0.2511	76.3405	<.0001	MLE
8	2	treatment	Hydromorphone	1	0.0155	0.1458	0.0113	0.9155	MLE
9	2	location	JH	1	-0.5374	0.4260	1.5915	0.2071	MLE
10	2	location	MUMC	1	0.0318	0.3537	0.0081	0.9284	MLE

Any help on how to obtain the final overall odds ratios and corresponding 95% CIs and pvalues would be much appreciated.

[Thuva]

I just wanted to add what my dataset 'lgscovb' looked like as well. For some reason I am getting so many intercepts.

proc print data=lgscovb ; run;

SAS Output

Obs	_Imputation_	Parameter	Intercept_1	Intercept_No	treatmentHydromorphone	locationJH	locationMUMC	Intercept__95	Intercept_0_9	Intercept_1_5	Intercept__87
1	1	Intercept_1	1.046096	0.060924	-0.00073	0.056477	-0.0008	.	.	.	.
2	1	Intercept_No	0.060924	0.063049	-0.00067	0.055415	-0.00096	.	.	.	.
3	1	treatmentHydromorphone	-0.00073	-0.00067	0.021264	-0.00005	-0.00032	.	.	.	.
4	1	locationJH	0.056477	0.055415	-0.00005	0.181463	-0.11747	.	.	.	.
5	1	locationMUMC	-0.0008	-0.00096	-0.00032	-0.11747	0.125081	.	.	.	.
6	2	Intercept__95	.	0.060924	-0.00073	0.056477	-0.0008	1.046096	.	.	.
7	2	Intercept_No	.	0.063049	-0.00067	0.055415	-0.00096	0.060924	.	.	.
8	2	treatmentHydromorphone	.	-0.00067	0.021264	-0.00005	-0.00032	-0.00073	.	.	.
9	2	locationJH	.	0.055415	-0.00005	0.181463	-0.11747	0.056477	.	.	.
10	2	locationMUMC	.	-0.00096	-0.00032	-0.11747	0.125081	-0.0008	.	.	.
11	3	Intercept_0_9	.	0.060924	-0.00073	0.056477	-0.0008	.	1.046096	.	.
12	3	Intercept_No	.	0.063049	-0.00067	0.055415	-0.00096	.	0.060924	.	.
13	3	treatmentHydromorphone	.	-0.00067	0.021264	-0.00005	-0.00032	.	-0.00073	.	.
14	3	locationJH	.	0.055415	-0.00005	0.181463	-0.11747	.	0.056477	.	.
15	3	locationMUMC	.	-0.00096	-0.00032	-0.11747	0.125081	.	-0.0008	.	.
16	4	Intercept_1_5	.	0.060924	-0.00073	0.056477	-0.0008	.	.	1.046096	.
17	4	Intercept_No	.	0.063049	-0.00067	0.055415	-0.00096	.	.	0.060924	.
18	4	treatmentHydromorphone	.	-0.00067	0.021264	-0.00005	-0.00032	.	.	-0.00073	.
19	4	locationJH	.	0.055415	-0.00005	0.181463	-0.11747	.	.	0.056477	.
20	4	locationMUMC	.	-0.00096	-0.00032	-0.11747	0.125081	.	.	-0.0008	.
21	5	Intercept__87	.	0.060924	-0.00073	0.056477	-0.0008	.	.	.	1.046096
22	5	Intercept_No	.	0.063049	-0.00067	0.055415	-0.00096	.	.	.	0.060924
23	5	treatmentHydromorphone	.	-0.00067	0.021264	-0.00005	-0.00032	.	.	.	-0.00073
24	5	locationJH	.	0.055415	-0.00005	0.181463	-0.11747	.	.	.	0.056477
25	5	locationMUMC	.	-0.00096	-0.00032	-0.11747	0.125081	.	.	.	-0.0008