standardize function

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 <- 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)

See Also

meanCenter which will center or re-scale only numberic variables

Author(s)

Paul Johnson pauljohn@ku.edu

  • Maintainer: Paul E. Johnson
  • License: GPL (>= 3.0)
  • Last published: 2022-08-06

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