There is quite some content online interpreting odds in a logistic model with a dichotomous predictor. My problem is understanding coefficients when there are more than 2 levels for a categorical variable. How do you define the odds then?
Data: X is a single categorical predictor with 4 levels: teenager, adult, mature, senior. Y: 1=smoking, 0=non smoking. LR: We use n-1 dummy variables. I chose adult as the reference bin as it had the highest concentration. (ok??) ________ | Intercepts | p adult | -4.3801 | 0 teenager | -0.32456 | 0 mature | 1.45119 | 0 old | -0.9891 | 0
Interpreting the coefficients
Teenager: Teen is less likely to smoke (w.r.t adult?). In fact, a teen is 28% (exp-0.32456 -1) less likely to smoke THAN AN ADULT. Is odds of teenager smoking always mentioned against the reference group?
Mature: Matures is more to smoke (w.r.t adult?). In fact, a mature is 326% more likely to smoke THAN AN ADULT. Is odds of mature smoking always mentioned against the reference group?