# rescale: Function for Standardizing by Centering and Dividing by 2... In arm: Data Analysis Using Regression and Multilevel/Hierarchical Models

## Description

This function standardizes a variable by centering and dividing by 2 sd's with exceptions for binary variables.

## Usage

 `1` ```rescale(x, binary.inputs="center") ```

## Arguments

 `x` a vector `binary.inputs` options for standardizing binary variables, default is `center`; `0/1` keeps original scale; `-0.5,0.5` rescales 0 as -0.5 and 1 as 0.5; `center` substracts the mean; and `full` substracts the mean and divids by 2 sd.

## Value

the standardized vector

## Author(s)

Andrew Gelman [email protected]; Yu-Sung Su [email protected]

## References

Andrew Gelman. (2008). “Scaling regression inputs by dividing by two standard deviations”. Statistics in Medicine 27: 2865–2873. http://www.stat.columbia.edu/~gelman/research/published/standardizing7.pdf

`standardize`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ``` # Set up the fake data n <- 100 x <- rnorm (n, 2, 1) x1 <- rnorm (n) x1 <- (x1-mean(x1))/(2*sd(x1)) # standardization x2 <- rbinom (n, 1, .5) b0 <- 1 b1 <- 1.5 b2 <- 2 y <- rbinom (n, 1, invlogit(b0+b1*x1+b2*x2)) rescale(x, "full") rescale(y, "center") ```