topic Re: Interpretation of exponentiated coefficient for categorical variable in EMiner logistic regressi in SAS Data Science

Interpretation of exponentiated coefficient for categorical variable in EMiner logistic regression?

PatrickHall — Fri, 19 Feb 2016 16:28:24 GMT

What is the interpretation of the highlighted value in the image below?

I understand that in the odds ratio table (not pictured), the displayed value for this level of the categorical variable will be different because it will be compared to a reference level. But what does it mean here exactly - when not compared to a reference level?

Re: Interpretation of exponentiated coefficient for categorical variable in EMiner logistic regressi

Reeza — Fri, 19 Feb 2016 16:50:35 GMT

It should be the same as your odds ratio table, and it should be for a specific level against reference table, assuming you've set the coding system to be the same.

In this case it looks like it's Level=0 against whatever your reference is.

If the variable is an indicator variable with 2 levels this makes sense.

If you're not getting the same as your odds ratio it's likely because you haven't specified the categorical variables to use the referential=PARAM coding system, but the GLM coding system.

http://support.sas.com/documentation/cdl/en/stathpug/68163/HTML/default/viewer.htm#stathpug_introcom_stat_sect010.htm

Re: Interpretation of exponentiated coefficient for categorical variable in EMiner logistic regressi

PatrickHall — Fri, 19 Feb 2016 17:08:46 GMT

I liked your suggestion, so I tried changing the input coding. Under Model Options -> Input Coding -> GLM.

With deviation coding the values are not the same:

Analysis of Maximum Likelihood Estimates
Parameter DF Estimate Error Chi-Square Pr > ChiSq Estimate Exp(Est)

M_DemAge 0 1 0.0741 0.0344 4.65 0.0311 1.077

Odds Ratio Estimates
Point Effect Estimate

M_DemAge 0 vs 1 1.160

With GLM coding, the values are the same. Thanks!!

Analysis of Maximum Likelihood Estimates
Parameter DF Estimate Error Chi-Square Pr > ChiSq Estimate Exp(Est)

M_DemAge 0 1 0.1389 0.0794 3.06 0.0802 1.149

Odds Ratio Estimates
Point Effect Estimate

M_DemAge 0 vs 1 1.149

Re: Interpretation of exponentiated coefficient for categorical variable in EMiner logistic regressi

Reeza — Fri, 19 Feb 2016 17:24:41 GMT

Yeah, that's what I was trying to say in a roundabout way 🙂