set.seed(1234)
x <- rnorm(1000)
y <- rbinom(1000, 1, exp(-2.3 + 0.1*x)/(1+exp(-2.3 + 0.1*x)))

fit = glm(y ~ x, family=binomial(link='logit'))
fit$coefficients

p = sum(y)/length(y)
z = rep(p, 1000)
z_star = log(z/(1-z))
fit2 = lm(z_star ~ x)
fit2$coefficients

> fit$coefficients
(Intercept)           x
 -2.2261215   0.1651474

> fit2$coefficients
  (Intercept)             x
-2.219647e+00 -5.338566e-16