standardize: Standardize values of an scdf file

In scan: Single-Case Data Analyses for Single and Multiple Baseline Designs

Standardize values of an scdf file

Description

This function is superseded by the much more versatile transform.scdf function (see example below). This function scales the measured values of an scdf file. It allows for mean centering and standardization based on each single-case data set or a scaling across all cases included in an scdf.

Usage

standardize(
  data,
  var,
  center = TRUE,
  scale = FALSE,
  m = 0,
  sd = 1,
  grand = TRUE
)

Arguments

data	A single-case data frame. See scdf() to learn about this format.
var	A character string or a vector of character strings with variable names that should be scaled.
center	If set TRUE, data are mean centered.
scale	If set TRUE, the standard deviation is set.
m	The target mean for centering.
sd	The target standard deviation for scaling
grand	If set TRUE, scaling is based on the mean and standard deviation of all values across all single-cases within the scdf.

Value

An scdf with the scaled values.

Author(s)

Juergen Wilbert

See Also

Other data manipulation functions: add_l2(), as.data.frame.scdf(), as_scdf(), fill_missing(), moving_median(), outlier(), ranks(), scdf(), select_cases(), set_vars(), shift(), smooth_cases(), truncate_phase()

Examples

## Standardize a multiple case scdf and compute an hplm
exampleAB_50 %>%
  standardize("values", center = TRUE, scale = TRUE) %>%
  hplm()

## The more versatile transform function supersedes standardize:
exampleAB_50 %>%
  transform(values = (values - mean(all(values))) / sd(all(values))) %>%
  hplm()

scan documentation built on Aug. 8, 2023, 5:07 p.m.