Standardize numeric and factor variables (z-scores)

This function standardizes variables to have mean of 0 and standard deviation of 1.

Usage

standardize(
  data,
  vars = everything(),
  flip = FALSE,
  keep_all = TRUE,
  outside_scale = c("Don't know", "Prefer not to say")
)

Arguments

data

A data frame containing variables to standardize.

vars

Variables to standardize. Supports tidyselect syntax (e.g., starts_with(), c(var1, var2)).

flip

Logical; if TRUE, reverses the direction of valid response levels before standardization.

keep_all

Logical; if TRUE, returns full dataset; if FALSE, returns only standardized variables.

outside_scale

Character vector of response levels (typically DK/PNTS) that lie outside of the scale and should be treated as neutral midpoint (0.5).

Value

A data frame with standardized variables.

• If keep_all = TRUE, the full dataset is returned with standardized variables.

• If keep_all = FALSE, only standardized variables are returned.

Details

• Numeric variables are z-scored.

• Factor variables are converted to numeric order and then standardized.

• Levels in outside_scale (e.g., Don't know) are assigned to the midpoint of the valid range before transformation.

Examples

# Standardize Q1 variable set with
standardize(data = data, vars = starts_with("Q1_"))
#> Error: These packages are required but not installed: tidyselect, dplyr

# Standardize Q1 and Q2 variable set with the scale order
standardize(data = data, vars = c(Q1, Q2), flip = TRUE)
#> Error: These packages are required but not installed: tidyselect, dplyr