I have an outcome variable, say Y and a list of 100 dimensions that could affect Y (say X1...X100).
After running my
You can get access the pvalues of the glm result through the function "summary". The last column of the coefficients matrix is called "Pr(>|t|)" and holds the pvalues of the factors used in the model.
Here's an example:
#x is a 10 x 3 matrix x = matrix(rnorm(3*10), ncol=3) y = rnorm(10) res = glm(y~x) #ignore the intercept pval summary(res)$coeff[-1,4] < 0.05