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TaylorRussell  

A Taylor-Russell Function for Multiple Predictors
View on CRAN: Click here


Download and install TaylorRussell package within the R console
Install from CRAN:
install.packages("TaylorRussell")

Install from Github:
library("remotes")
install_github("cran/TaylorRussell")

Install by package version:
library("remotes")
install_version("TaylorRussell", "1.2.1")



Attach the package and use:
library("TaylorRussell")
Maintained by
Niels Waller
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-30
Latest Update: 2023-12-04
Description:
The Taylor Russell model is a widely used method for assessing test validity in personnel selection tasks. The three functions in this package extend this model in a number of notable ways. TR() estimates test validity for a single selection test via the original Taylor Russell model. It extends this model by allowing users greater flexibility in argument choice. For example, users can specify any three of the four parameters (base rate, selection ratio, criterion validity, and positive predictive value) of the Taylor Russell model and estimate the remaining parameter (see the help file for examples).The TaylorRussell() function generalizes the original Taylor Russell model to allow for multiple selection tests (predictors).To our knowledge, this is the first generalization of the Taylor Russell model to allow for three or more selection tests (it is also the first to correctly handle models with two selection tests). TRDemo() is a 'shiny' program for illustrating the underlying logic of the Taylor Russell model. Taylor, HC and Russell, JT (1939) "The relationship of validity coefficients to the practical effectiveness of tests in selection: Discussion and tables" <doi:10.1037/h0057079>.
How to cite:
Niels Waller (2023). TaylorRussell: A Taylor-Russell Function for Multiple Predictors. R package version 1.2.1, https://cran.r-project.org/web/packages/TaylorRussell. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.2 (2023-11-30 21:40)
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