rockchalk (version 1.8.111)

standardize: Estimate standardized regression coefficients for all variables

Description

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.

Usage

standardize(model)
# S3 method for lm
standardize(model)

Arguments

model

a fitted lm object

Value

an lm fitted with the standardized variables

a standardized regression object

See Also

meanCenter which will center or re-scale only numberic variables

Examples

# NOT RUN {
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)

# }