Suppose that the model had the following output:
Estimate Std. Error z value Pr(>|z|) (Intercept) 0.07 0.33 0.21 0.829 x0_low 0.44 0.22 1.96 0.049 * x1_m -0.51 0.25 -1.98 0.047 * x1_l -0.05 0.22 -0.24 0.809 x2_no 0.51 0.26 1.94 0.051 .
s, m, l
I'm wondering what an interpretation for the coefficient
x1_m would be.
It seems as though it could be:
x1_m reduces the
log(odds) by roughly 40% having adjusted for
But what I'm a bit confused about is whether this is actually what it's saying,
x1_m is simply a level within the factor
x1, so does that change its