jtools (version 2.1.0)

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.

Value

A transformed version of the data argument.

Details

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

See Also

Other standardization: center_mod(), center(), gscale(), scale_mod()

Examples

# NOT RUN {
# Standardize just the "qsec" variable in mtcars
standardize(mtcars, vars = "qsec")

# }