self_standardize: Standardize circumplex scales using sample data

In jmgirard/ssm: Analysis and Visualization of Circular Data

Standardize circumplex scales using sample data

Description

Take in a data frame containing circumplex scales (or items) and return that same data frame with each specified variable transformed into standard scores (i.e., z-scores) based on observed means and SDs.

Usage

self_standardize(
  data,
  scales,
  na.rm = TRUE,
  prefix = "",
  suffix = "_z",
  append = TRUE
)

Arguments

data	Required. A data frame or matrix containing at least circumplex scales.
scales	Required. A character vector containing the column names, or a numeric vector containing the column indexes, for the variables (scale scores) to be standardized.
na.rm	Optional. A logical that determines whether to remove missing values from scales when calculating the means and SDs used for standardization (default = TRUE).
prefix	Optional. A string to include at the beginning of the newly calculated scale variables' names, before the scale name and suffix (default = "").
suffix	Optional. A string to include at the end of the newly calculated scale variables' names, after the scale name and prefix (default = "_z").
append	Optional. A logical that determines whether the calculated standardized scores should be added as columns to data in the output or the standardized scores alone should be output (default = TRUE).

Value

A data frame that contains the self-standardized versions of scales.

See Also

Other tidying functions: ipsatize(), norm_standardize(), score()

Examples

self_standardize(aw2009, scales = 1:8)

jmgirard/ssm documentation built on June 13, 2025, 8:59 p.m.