Estimate standardized regression coefficients for all variables
Estimate standardized regression coefficients for all variables
This is brain-dead standardization of all variables in the design matrix. It mimics the silly output of SPSS, which standardizes all regressors, even if they represent categorical variables.
standardize(model)## S3 method for class 'lm'standardize(model)
Arguments
model: a fitted lm object
Returns
an lm fitted with the standardized variables
a standardized regression object
Examples
library(rockchalk)N <-100dat <- genCorrelatedData(N = N, means = c(100,200), sds = c(20,30), rho =0.4, stde =10)dat$x3 <- rnorm(100, m =40, s =4)m1 <- lm(y ~ x1 + x2 + x3, data = dat)summary(m1)m1s <- standardize(m1)summary(m1s)m2 <- lm(y ~ x1 * x2 + x3, data = dat)summary(m2)m2s <- standardize(m2)summary(m2s)m2c <- meanCenter(m2)summary(m2c)
See Also
meanCenter which will center or re-scale only numberic variables