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)
model |
a fitted lm object |
an lm fitted with the standardized variables
a standardized regression object
Paul Johnson <pauljohn@ku.edu>
meanCenter which will center or
re-scale only numberic variables
library(rockchalk) N <- 100 dat <- 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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.