jtools: standardize – R documentation

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standardize

Standardize vectors, data frames, and survey designs

Description

This function is a wrapper around gscale() that is configured to do a conventional standardization of continuous variables, mean-centering and dividing by one standard deviation.

Usage

standardize(
  data = NULL,
  vars = NULL,
  binary.inputs = "center",
  binary.factors = TRUE,
  weights = NULL
)

Arguments

`data`	A data frame or survey design. Only needed if you would like to rescale multiple variables at once. If `x = NULL`, all columns will be rescaled. Otherwise, `x` should be a vector of variable names. If `x` is a numeric vector, this argument is ignored.
`vars`	If `data` is a data.frame or similar, you can scale only select columns by providing a vector column names to this argument.
`binary.inputs`	Options for 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` subtracts the mean; and `full` subtracts the mean and divides by 2 sd.
`binary.factors`	Coerce two-level factors to numeric and apply scaling functions to them? Default is TRUE.
`weights`	A vector of weights equal in length to `x`. If iterating over a data frame, the weights will need to be equal in length to all the columns to avoid errors. You may need to remove missing values before using the weights.

Details

Some more information can be found in the documentation for gscale()

Value

A transformed version of the data argument.

Examples

# Standardize just the "qsec" variable in mtcars
standardize(mtcars, vars = "qsec")

jtools

Analysis and Presentation of Social Scientific Data

v2.1.3

MIT + file LICENSE

Authors

Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)

Initial release