PROC LOGISTIC DATA=SASUSER.MODS5

PLOTS(ONLY)=ALL

;

CLASS Race_W (ref ="1") HISP (REF= "1") PRIVPUB1 (REF="0") EDDUMMY (REF="1") FEMDUMMY (REF="1")/PARAM=REF ;

MODEL LOGDUM (Event = '1')=Age Race_W HISP PRIVPUB1 EDDUMMY FEMDUMMY /

SELECTION=NONE

LINK=LOGIT

;

RUN;

QUIT;

The odds ratio table generates in part

EDDUMMY 0 VS 1 1.427

PRIVDUMMY 1 vs 0 2.199

Do you interpret this (the SAS results confuse me) that for EDDUMMY if the predictor takes on a value of 0 the event is 1.427 times more likely. And for PrivDummy if the predictor takes on the value of 1 the event is 2.199 times more likely?

In terms of interpreting the substantive impact I am less clear what is a large effect for logistic regression than linear (what is a large effect is more intuitively obvious to me for linear regression). When I see effects near 1 (for example race has a value of 1.062) I see this as a small effect size (since 1 is similar in logistic regression to 0 in linear regression as showing no effect size).