Package: mstR 1.2

David Magis

mstR: Procedures to Generate Patterns under Multistage Testing

Generation of response patterns under dichotomous and polytomous computerized multistage testing (MST) framework. It holds various item response theory (IRT) and score-based methods to select the next module and estimate ability levels (Magis, Yan and von Davier (2017, ISBN:978-3-319-69218-0)).

Authors:David Magis, Duanli Yan, Alina von Davier

mstR_1.2.tar.gz
mstR_1.2.tar.gz(r-4.5-noble)mstR_1.2.tar.gz(r-4.4-noble)
mstR_1.2.tgz(r-4.4-emscripten)mstR_1.2.tgz(r-4.3-emscripten)
mstR.pdf |mstR.html✨
mstR/json (API)
NEWS

# Install 'mstR' in R:

install.packages('mstR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

19 exports 3 stars 0.23 score 0 dependencies 17 scripts 150 downloads

Last updated 6 years agofrom:8b6b9af43a. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Aug 23 2024
R-4.5-linux	OK	Aug 23 2024

Exports:eapEst eapSem genDichoMatrix genPattern genPolyMatrix Ii integrate.mstR Ji MKL MWMI nextModule Pi plot.mst print.mst randomMST semTheta startModule testListMST thetaEst

Dependencies:

Citation

Readme and manuals

Help Manual

Help page	Topics
EAP ability estimation (dichotomous and polytomous IRT models)	eapEst
Standard error of EAP ability estimation (dichotomous and polytomous IRT models)	eapSem
Item bank generation (dichotomous models)	genDichoMatrix
Random generation of item response patterns under dichotomous and polytomous IRT models	genPattern
Item bank generation (polytomous models)	genPolyMatrix
Item information functions, first and second derivatives (dichotomous and polytomous models)	Ii
Numerical integration by linear interpolation (for mstR internal use)	integrate.mstR
Function J(theta) for weighted likelihood estimation (dichotomous and polytomous IRT models)	Ji
Module Kullback-Leibler (MKL) and posterior module Kullback-Leibler (MKLP)	MKL
Maximum likelihood weighted module information (MLWMI) and maximum posterior weighted module information (MPWMI)	MWMI
Selection of the next module in MST	nextModule
Item response probabilities, first, second and third derivatives (dichotomous and polytomous models)	Pi
Random generation of multistage tests (dichotomous and polytomous models)	plot.mst print.mst randomMST
Standard error of ability estimation (dichotomous and polytomous models)	semTheta
Selection of the first module in MST	startModule
Testing the format of the MST input lists	testListMST
Ability estimation (dichotomous and polytomous models)	thetaEst

Package: mstR 1.2

mstR: Procedures to Generate Patterns under Multistage Testing

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)