glm p-values on features

mydf <- data.frame(x1=rnorm(100), x2=rnorm(100), x3=rnorm(100))
mydf$y <- 0.5 * mydf$x1 + 3 * mydf$x3 + rnorm(100)
 
fit <- glm( y ~ . , data=mydf )
coefficients( summary(fit) )
                Estimate Std. Error    t value     Pr(>|t|)
  (Intercept) -0.2385855  0.2541498 -0.9387593 3.502103e-01
x1           0.6956811  0.1330900  5.2271462 1.003295e-06
x2           0.1313823  0.1417679  0.9267420 3.563846e-01
x3           2.7986410  0.4531338  6.1761919 1.576173e-08

Dear list,

does anyone know how to get p-values on the coefficients returned by
glm?

thanks+greets,
Joost

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