m1 <- glm(sit/n ~ confed, weights=n, family='binomial', data=d) 
summary(m1) 


pred <- predict(m1, data.frame(confed=c(0,1)), type='response', se.fit=TRUE) 

pred$fit
pred$se.fit

with(pred, cbind(fit, low = fit - 1.96*se.fit, up = fit + 1.96*se.fit))