ipsatize: Ipsatize circumplex items using deviation scoring across...

In jmgirard/circumplex: Analysis and Visualization of Circular Data

Ipsatize circumplex items using deviation scoring across variables

Description

Rescore each circumplex item using deviation scoring across variables. In other words, subtract each observation's mean response from each response. This effectively removes the presence of a general factor, which can make certain circumplex fit analyses more powerful.

Usage

ipsatize(.data, items, na.rm = TRUE, overwrite = FALSE)

Arguments

.data	Required. A data frame containing at least circumplex scales.
items	Required. The variable names or column numbers for the variables in .data that contain circumplex items to be ipsatized.
na.rm	Optional. A logical that determines whether missing values should be ignored during the calculation of the mean during ipsatization (default = TRUE).
overwrite	Optional. A logical that determines whether the variables specified in items should be overwritten with ipsatized versions or alternatively preserved and new variables ending with "_i" should be added to the data frame (default = FALSE).

Value

A data frame that matches .data except that the variables specified in items have been rescored using ipsatization.

See Also

Other tidying functions: score(), standardize()

Examples

data("raw_iipsc")
ipsatize(raw_iipsc, IIP01:IIP32)

jmgirard/circumplex documentation built on Aug. 31, 2023, 8:03 a.m.