This function takes in a dataframe, the name of any number of variables. It then returns either a vector or a dataframe of scaling results. If passed a single variable name, standardize will return a the standardized variable as a vector, when passed 2 or more variable names, standardize will return a data frame containing all of the standardized variables.
Usage
standardize(data, variable, type = "absolute")
Arguments
data
data.frame object that contains both the dependent variable and predictor variables you want to regress.
variable
variable name or vector of names for variables you want standardized.
type
by default, 'absolute' will scale every variable from 0 to 1. "classic" is a little more complicated where the variable is rescaled the mean equaling 0 and a standard deviation is 1.
Value
if the function is passed a single variable to standardize, it will return a vector of all obeservations in the variable standardized. If the function is passed more than one variable name, it will return a data-frame containing the new observation values.
Details
Often times we are forced to compare variables which exist on different scales, but how do you compare the coefficient for a country's population to one that's much smaller? Standardizing your variables can make reading regression results more useful because it will make coeficients more comparable.