Hi everyone! I am fairly new to SAS and am looking for some help debugging my code. For background, I have a dataset of 102 subjects. I am running a log-binomial regression to determine prevalence ratios. My outcome variable is 'comfort' which is binary, with the outcome of interest being 'comfortable=1'. My predictor variables is race/ethnicity and is nominal, coded as 1, 2, 3, and 4 (for different race/ethnicities). I am looking to get estimates of the PR and 95% CI for each group of the predictor variable compared to the referent group.
I am using the following code, however, the table of 'Contrast Estimate Results' returns a result of 'Non-est' for each estimate statement. Note, due to convergence issues I am using a poisson distribution with the repeated subject line.
proc genmod data=final;
class id race_eth_grp(ref='1');
model vagina_comfort_bin(event='1')= race_eth_grp
/ dist=poisson link=log;
repeated subject=id / type=unstr;
estimate 'PR: race_eth_grp 2 vs. 1' race_eth_grp 0 1 0 0 / exp;
estimate 'PR: race_eth_grp 3 vs. 1' race_eth_grp 0 0 1 0 / exp;
estimate 'PR: race_eth_grp 4 vs. 1' race_eth_grp 0 0 0 1 / exp;
run;
I'm not sure what I am doing wrong and would gladly appreciate any insight. It may be important to note the skewed distribution among groups for 'race_eth_grp', with race_eth_grp=1 having 84 subjects, race_eth_grp=2 having 5 subjects, race_eth_grp=3 having 5 subjects, and race_eth_grp=4 having 8 subjects (*note this is the overall count, not the prevalence that responded comfortable to the outcome). I've tried the Firth method as well using proc logistic, however I am still running in to issues. Please let me know if any additional information is needed to help answer this! Thank you!!
