rockchalk (version 1.4)

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 class 'lm':
standardize(model)

Arguments

model

a fitted lm object

Value

• an lm fitted with the standardized variables

  a standardized regression object

Examples

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)