glm() and lm()

In R, using lm() is a special case of glm().

lm() fits models following the form Y = Xb + e, where e is Normal (0 , s^2).

glm() fits models following the form f(Y) = Xb + e. However, in glm both the function f(Y) (the ‘link function’) and the distribution of the error term e can be specified. Hence the name - ‘generalised linear model’.

If you are getting the same results using both lm() and glm(), it is because for glm(), f(Y) defaults to Y, and e defaults to Normal (0, s^2). i.e. if you don’t specify the link function and error distribution, the parameters that glm() uses produce the same effect as running lm().