SDT (version 1.0.0)

internalization: Motivation Internalization or Externalization Shares

Description

internalization computes the internalization or externalization shares of an intermediate motivation regulation type with respect to the poles of intrinsic regulation and external regulation as the reference system.

Usage

internalization(intermediate_regulation, intrinsic_regulation,
  external_regulation)

Arguments

intermediate_regulation

A required numeric vector of intermediate, either identified or introjected, regulation subscale motivation scores. No NA, NaN, Inf, or -Inf values are allowed.

intrinsic_regulation, external_regulation

Required numeric vectors of intrinsic regulation and external regulation subscale motivation scores, respectively. No NA, NaN, Inf, or -Inf values are allowed.

Value

If the arguments intermediate_regulation, intrinsic_regulation, and external_regulation are of required types, internalization returns a numeric vector containing the \(2\) named components internal share and external share of the intermediate_regulation type with respect to the extreme poles intrinsic_regulation and external_regulation of the theory. The returned object is of the class share and has the attribute analysis set to have the value internalization.

Details

This function computes the shares of motivation internalization or externalization pertaining to the notion of “somewhat internal” and “somewhat external” on the self-determination theory subscales of identified regulation and introjected regulation, as the intermediate motivation regulation types---with respect to intrinsic regulation and external regulation, the completely internal and completely external motivation poles of the theory, respectively, as the reference system spanned by these two base elements.

The argument intermediate_regulation, the target variable of the constrained regression analysis, can be either identified regulation or introjected regulation aggregate subscale motivation scores, and the arguments intrinsic_regulation and external_regulation, the predictor variables of the constrained regression analysis, do represent aggregate motivation scores for the intrinsic regulation and external regulation subscales, respectively. The function solve.QP of the package quadprog is applied in internalization to solve the self-determination theory related (convex) quadratic program. For details, see Uenlue and Dettweiler (2015).

References

Uenlue, A. and Dettweiler, U. (2015) Motivation internalization and simplex structure in self-determination theory. Psychological Reports, 117(3), 675--691. URL https://doi.org/10.2466/14.PR0.117c25z1.

See Also

The two other main functions of the package: simplex for motivation simplex structure analysis; sdi for the original and adjusted SDI or RAI index. See the methods associated with internalization as the constructor function: plot.share, the S3 method for plotting objects of the class share; print.share, the S3 method for printing objects of the class share. See also SDT-package for general information about this package.

Examples

# NOT RUN {
## attach dataset to search path (to use variable names)
attach(learning_motivation)

## internal share and external share of identified regulation
(idr <- internalization(identified, intrinsic, external))
## attribute value and class
attr(idr, "analysis")
class(idr)

## internal share and external share of introjected regulation
(ijr <- internalization(introjected, intrinsic, external))
## all attributes
attributes(ijr)
# }