option to get expoentiated coefficients in proc mixed output?

[billi_billi]

I am  new to use and using PROC MIXED using clustered data to answer the question access to medical care is related to the risk. Below is my code in which predictors are different type of risk: income, education and insurance risk (1= risk,0=no risk) and risk_score is the cummulative risk of all the three risks (ranging from 0-6), and outcome here is doctor's office in vicinity (1=yes,0=no) and I am controlling for confounding factors age, race, gender. Observations are clustered so I am using random effect statement. This code is working fine but I also need exponentiated coefficients and 95% CI in my output. Is there any option to get those in the output. 

proc mixed data= data PLOTS(MAXPOINTS=NONE) method=type3;
class risk_score income_risk educ_risk insurance_risk  medical Race gender ;
model medical = age Race gender ;
random risk_score income_risk educ_risk insurance_risk ;
run;

Thank you in advance.

[PaigeMiller]

To get confidence intervals of the coefficients

model medical = age Race gender / solution cl;

I have never head of getting exponentiated coefficients, and I am not aware of any built in feature in PROC MIXED to do this, but you could certainly store the coefficients in a SAS data set, and then exponentiate them in a DATA step.

[billi_billi]

@PaigeMiller do you mind telling how to store coefficients in a SAS data set, and then exponentiate them in a DATA step or if there is any documentation that I can look up to do this?

[PaigeMiller]

ods output solutionf=coefficients;

before your PROC MIXED statement creates a SAS data set named COEFFICIENTS which contains ... well ... you know

Then you can exponentiate as desired in a SAS data set.

data coefficients1;
    set coefficients;
    exponentiated = estimate ** 2; /* for example, if you want them squared */
run;

[ed_sas_member]

Hi @billi_billi 

You can put 

	model medical=age Race gender / cl solution;