lm summary with beta coefficients

gistfile1.r

summary.with.betas <- function(model, logit=FALSE) {
  model <- update(model, x=TRUE, y=TRUE)
  sd.x <- apply(model$x, 2, sd)
  sd.y <- sd(model$y)
  std.coef <- coef(model) * (sd.x / sd.y)
  coef.table <- as.data.frame(summary(model)$coefficients)
  coef.table <- cbind(coef.table, beta=std.coef, sdX=sd.x)
  if (logit == TRUE) {
    e.beta <- exp(coefficients(model))
    e.bstdx <- exp(sd.x)
    coef.table <- cbind(coef.table, e.beta=e.beta, e.bstdx=e.bstdx)
  }
  coef.table
}

# Use it like this:
x <- runif(100, -1, 1)
y <- runif(100, -1, 1)
fit <- lm(y ~ x)

summary(fit)
summary.with.betas(fit)