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This function standardizes a variable by centering and dividing by 2 sd's with exceptions for binary variables.
rescale(x, binary.inputs="center")
a vector
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.
the standardized vector
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
# NOT RUN {
# 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")
# }
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