topic Re: How to calculate adjusted odds ratios and 95% CIs for GEE using proc genmod in Statistical Procedures

How to calculate adjusted odds ratios and 95% CIs for GEE using proc genmod

bsriv — Mon, 30 Oct 2017 03:20:02 GMT

Hi all- relatively new to SAS, and these forums have been really helpful, but I'm using a GEE (rather than logistic regression) because i have data with repeated measures and multiple predictors, but I can't figure out how to just have a basic table of ORs, 95% CIs, and p values. I have tried ESTIMATE and LSMEANS but it's not giving me what I want (the analyses look bivariate with both). Here is my model:

proc genmod data=work.opioid27;

class BJH_MedRec countx (ref="1") racex (ref="1") agegrp (ref="2") narcanx (ref="1") alcoholx (ref="1") moodx (ref="1") sudx (ref="1") yr (ref="2005") / param=ref;

model suicidex=countx racex agegrp narcanx alcoholx moodx sudx yr / dist=bin link=logit;

repeated subject=BJH_MedRec / type=cs;

run;

Thanks!

Re: How to calculate adjusted odds ratios and 95% CIs for GEE using proc genmod

Rick_SAS — Mon, 30 Oct 2017 17:48:13 GMT

Did you try using the EXP option on the ESTIMATE statement? See the GEE example on this web page.

Re: How to calculate adjusted odds ratios and 95% CIs for GEE using proc genmod

SAS_Rob — Mon, 30 Oct 2017 18:58:04 GMT

If you use the PARAM=GLM option on the CLASS statement then you will be able to use the ODDSRATIO option on the LSMEANS statement. These estimates will all be adjusted for the other effects in the model.

proc genmod data=work.opioid27;

class BJH_MedRec countx (ref="1") racex (ref="1") agegrp (ref="2") narcanx (ref="1") alcoholx (ref="1") moodx (ref="1") sudx (ref="1") yr (ref="2005") / param=glm;

model suicidex=countx racex agegrp narcanx alcoholx moodx sudx yr / dist=bin link=logit;

repeated subject=BJH_MedRec / type=cs;

lsmeans countx racex agegrp narcanx alcoholx moodx sudx yr/diff oddsratio cl;

run;

Re: How to calculate adjusted odds ratios and 95% CIs for GEE using proc genmod

bsriv — Mon, 30 Oct 2017 20:41:03 GMT

Thank you!