standardize {rockchalk} | R Documentation |
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
Author(s)
Paul Johnson pauljohn@ku.edu
See Also
meanCenter
which will center or
re-scale only numberic variables
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)
[Package rockchalk version 1.8.157 Index]