Hello,
I created different statistical models using demo data and need help interpreting/wording the odds ratio/output from Proc logistic simple terms. I have models with and without interactions. I appreciate any input as I am still learning to read output correctly. There are so many different ways to get Odds ratios that I worry about reading it incorrectly or am missing a step when it comes to inverted values.
Proc Logistic: Interaction Model Questions:
I used the exponentiated values from the Estimate value from the Analysis of Maximum Likelihood Estimates table, to calculate the Odds ratio (OR)
proc logistic data=Sashelp.Birthwgt plots(only)=(effect oddsratio) ;
class race (ref="White")somecollege(ref="No")/param=ref;
model LowBirthWgt (event="Yes")=somecollege|race/ clodds=pl selection=backward;
estimate 'Black, no college' race 0 1 somecollege 0/exp;
run;
Questions from a simple Logistic Model with No Interactions :
proc logistic data=Sashelp.Birthwgt plots(only)=(effect oddsratio) ;
class race (ref="White")somecollege(ref="No")/param=ref;
model LowBirthWgt (event="Yes")=somecollege race/ clodds=pl selection=backward;
run;
Lastly, I am using Proc glimmix for the first time.
proc glimmix data=Sashelp.Birthwgt;
class race (ref="White") somecollege(ref="No");
model LowBirthWgt (event="Yes") = somecollege*race/ dist=binary;
lsmeans somecollege*race / slicediff=somecollege oddsratio ilink;
run;
I apologize in advance for the long post, if it's better to break up the questions in the future, please advise. I learn best by seeing examples and annotated output, which I've had difficulty finding for this. Any recommendations on resources like this are welcome. Thank you for helping out a rookie!
See this note on computing and interpreting odds ratio estimates in a model with interaction. It discusses both LOGISTIC and GLIMMIX. It shows multiple ways to compute odds ratios in PROC LOGISTIC. In short, you do not exponentiate interaction parameters - an interaction means that the effect of one variable depends on the level of the other regardless of the type of model. So, in a logistic model, you need to compute odds ratios for one variable at given levels of the other. An odds ratio estimate of, say, 2 means that the odds of the event for the group in the numerator is twice the event odds for the group in the denominator. If you want to interpret it as a percent change from the denominator group, use the odds ratio minus 1 and then multiply by 100.
Thank you for the link- do you know if there there are any other resources with more examples by any chance?
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