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GPCMlasso  

Differential Item Functioning in Generalized Partial Credit Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("GPCMlasso", "0.1-7")



Attach the package and use:
library("GPCMlasso")
Maintained by
Gunther Schauberger
[Scholar Profile | Author Map]
First Published: 2018-02-12
Latest Update: 2024-01-23
Description:
Provides a framework to detect Differential Item Functioning (DIF) in Generalized Partial Credit Models (GPCM) and special cases of the GPCM as proposed by Schauberger and Mair (2019) . A joint model is set up where DIF is explicitly parametrized and penalized likelihood estimation is used for parameter selection. The big advantage of the method called GPCMlasso is that several variables can be treated simultaneously and that both continuous and categorical variables can be used to detect DIF.
How to cite:
Gunther Schauberger (2018). GPCMlasso: Differential Item Functioning in Generalized Partial Credit Models. R package version 0.1-7, https://cran.r-project.org/web/packages/GPCMlasso. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1-1 (2018-02-12 19:23), 0.1-2 (2018-08-02 18:00), 0.1-3 (2019-02-21 09:30), 0.1-4 (2019-04-02 13:33), 0.1-5 (2021-05-21 09:30), 0.1-6 (2022-05-03 13:10)
Other packages that cited GPCMlasso R package
View GPCMlasso citation profile
Other R packages that GPCMlasso depends, imports, suggests or enhances
Complete documentation for GPCMlasso
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