I have performed a logistic regression with the following result:
ssi.logit.single.age[\"coefficients\"]
# $coefficients
# (Intercept) age
# -3.425062
I've found it, from here
Look at the data structure produced by summary()
> names(summary(lm.D9))
[1] "call" "terms" "residuals" "coefficients"
[5] "aliased" "sigma" "df" "r.squared"
[9] "adj.r.squared" "fstatistic" "cov.unscaled"
Now look at the data structure for the coefficients in the summary:
> summary(lm.D9)$coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.032 0.2202177 22.850117 9.547128e-15
groupTrt -0.371 0.3114349 -1.191260 2.490232e-01
> class(summary(lm.D9)$coefficients)
[1] "matrix"
> summary(lm.D9)$coefficients[,3]
(Intercept) groupTrt
22.850117 -1.191260