How can I get odds ratio estimates and confidence intervals for multiple levels with a variable

[lindsaypaige]

Hi all, 

I am using SAS Studio. I'm trying to compute the odds ratios and confidence intervals for all of the levels within a variable. For example, I am looking at how maltreatment exposure predicts chronic pain. Maltreatment exposure has four levels: 1, 2, 3, and 4, to indicate frequency of occurrence. I want to see what the odds are for developing chronic pain if someone has a maltreatment frequency of 1, a maltreatment frequency of 2, and so on. I have tried both PROC LOGISTIC and PROC GLIMMIX, but I only get one odds ratio, instead of an odds ratio for each level of the variable. 

My predictors include age (8-19 years), gender (0 or 1), placement type (1 or 1), and maltreatment exposure (1,2,3,and 4). My outcome is chronic pain (0 or 1). I would like to look at the odds of chronic pain for all of the levels of all of my variables. 

TITLE1 "Single-Level Logistic Model Predicting Chronic Pain";
PROC GLIMMIX DATA=work.pain NOCLPRINT NAMELEN=100 METHOD=QUAD (QPOINTS=15) GRADIENT;
CLASS PID; * Descending makes us predict the 1 instead of the default-predicted 0;
MODEL chronicpain (DESCENDING) = age_c Gender GroupHome RndChron_c / SOLUTION LINK=LOGIT DIST=BINARY DDFM=Satterthwaite ODDSRATIO;
ESTIMATE "Intercept" intercept 1 / ILINK; * ILINK is inverse link (to un-logit);
ESTIMATE "Chronic Pain if Age=9" intercept 1 age_c 1 / ILINK;
ESTIMATE "Chronic Pain if Age=10" intercept 1 age_c 2 / ILINK;
RUN;

Thanks for your help!

Lindsay 

[PGStats]

Your code doesn't include any reference to maltreatment and your model doesn't include any reference to PID...

Assuming that all your independent variables are classes, you could start with:

TITLE1 "Single-Level Logistic Model Predicting Chronic Pain";

PROC GLIMMIX DATA=work.pain NOCLPRINT NAMELEN=100 METHOD=QUAD (QPOINTS=15) GRADIENT;
CLASS age_c Gender GroupHome RndChron_c; 
MODEL chronicPain (event="1") = age_c Gender GroupHome RndChron_c / SOLUTION LINK=LOGIT DIST=BINARY DDFM=Satterthwaite;
lsmeans age_c / oddsratio;
lsmeans gender / oddsratio;
lsmeans groupHome / oddsratio;
lsmeans RndChron_c / oddsratio;
RUN;

(untested)