其中的lm.beta其实是：

function (MOD) 

{

    b <- summary(MOD)$coef[-1, 1]

    sx <- sd(MOD$model[-1])

    sy <- sd(MOD$model[1])

    beta <- b * sx/sy

    return(beta)

}

Advantages

Standard coefficients' advocates note that the coefficients ignore the independent variable's scale of units, which makes comparisons easy.

Disadvantages

Critics voice concerns that such a standardization can be misleading; a change of one standard deviation in one variable has no reason to be equivalent to a similar change in another predictor.

Some variables are easy to affect externally, e.g., the amount of time spent on an action. Weight or cholesterol level are more difficult, and some, like height or age, are impossible to affect externally.