Is it possible to set a stepwise linear model to use the BIC criteria rather than AIC?
I've been trying this but it still calculates each step using AIC values rather than BIC
null = lm(data[,1] ~ 1)
full = lm(data[,1] ~ age + bmi + gender + group)
step(null, scope = list(lower=null,upper=full),
direction="both", criterion = "BIC")
Add the argument k=log(n)
to the step
function (n
number of samples in the model matrix)
From ?step
:
Arguments:
...k the multiple of the number of degrees of freedom used for the penalty. Only k = 2 gives the genuine AIC; k = log(n) is sometimes referred to as BIC or SBC.