Package: irtQ 0.2.1

irtQ: Unidimensional Item Response Theory Modeling

Fit unidimensional item response theory (IRT) models to a mixture of dichotomous and polytomous data, calibrate online item parameters (i.e., pretest and operational items), estimate examinees' abilities, and examine the IRT model-data fit on item-level in different ways as well as provide useful functions related to IRT analyses such as IRT model-data fit evaluation and differential item functioning analysis. The bring.flexmirt() and write.flexmirt() functions were written by modifying the read.flexmirt() function (Pritikin & Falk (2022) <doi:10.1177/0146621620929431>). The bring.bilog() and bring.parscale() functions were written by modifying the read.bilog() and read.parscale() functions, respectively (Weeks (2010) <doi:10.18637/jss.v035.i12>). The bisection() function was written by modifying the bisection() function (Howard (2017, ISBN:9780367657918)). The code of the inverse test characteristic curve scoring in the est_score() function was written by modifying the irt.eq.tse() function (González (2014) <doi:10.18637/jss.v059.i07>). In est_score() function, the code of weighted likelihood estimation method was written by referring to the Pi(), Ji(), and Ii() functions of the catR package (Magis & Barrada (2017) <doi:10.18637/jss.v076.c01>).

Authors:Hwanggyu Lim [aut, cre], Craig S. Wells [ctb], James Howard [ctb], Joshua Pritikin [ctb], Jonathan P Weeks [ctb], Jorge González [ctb], David Magis [ctb]

irtQ_0.2.1.tar.gz
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irtQ_0.2.1.tgz(r-4.4-any)irtQ_0.2.1.tgz(r-4.3-any)
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irtQ.pdf |irtQ.html✨
irtQ/json (API)
NEWS

# Install 'irtQ' in R:
install.packages('irtQ', repos = c('https://hwangq.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • LSAT6 - LSAT6 data
  • simCAT_DC - Simulated single-item format CAT Data
  • simCAT_MX - Simulated mixed-item format CAT Data
  • simMG - Simulated multiple-group data
  • simMST - Simulated 1-3-3 MST panel data

On CRAN:

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

33 exports 1 stars 0.23 score 94 dependencies 2 scripts 204 downloads

Last updated 23 days agofrom:a09fafed86. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-winOKAug 26 2024
R-4.5-linuxOKAug 26 2024
R-4.4-winOKAug 26 2024
R-4.4-macOKAug 26 2024
R-4.3-winOKAug 26 2024
R-4.3-macOKAug 26 2024

Exports:bind.fillbisectionbring.bilogbring.flexmirtbring.mirtbring.parscalecac_leecac_rudcatsibcovirtdrmest_irtest_itemest_mgest_scoregen.weightgetirtgrdifinfoirtfitllike_scorelwrcpcd2prmrdifreval_mstrun_flexmirtshape_dfsimdatsummarysx2_fittracelinewrite.flexmirt

Dependencies:audiobeeprbriocallrcliclustercodetoolscolorspacecpp11crayoncurldcurverDerivdescdiffobjdigestdplyrevaluatefansifarverfsfuturefuture.applygenericsggplot2globalsglueGPArotationgridExtragtablehmsisobandjanitorjsonlitelabelinglatticelifecyclelistenvlubridatemagrittrMASSMatrixmgcvmirtmunsellnlmeparallellypbapplypermutepillarpkgbuildpkgconfigpkgloadplyrpraiseprocessxprogressrpspurrrR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratrematch2reshape2RfastrlangrprojrootRPushbulletscalessessioninfoSimDesignsnakecasesnowstatmodstringistringrtestthattibbletidyrtidyselecttimechangeutf8vctrsveganviridisLitewaldowithr

Readme and manuals

Help Manual

Help pageTopics
irtQ: Unidimensional Item Response Theory ModelingirtQ-package irtQ
Bind Fillbind.fill
The bisection method to find a rootbisection
Import Item and Ability Parameters from IRT Softwarebring.bilog bring.flexmirt bring.mirt bring.parscale
Classification accuracy and consistency using Lee's (2010) approach.cac_lee
Classification accuracy and consistency using Rudner's (2001, 2005) approach.cac_rud
CATSIB DIF detection procedurecatsib
Asymptotic variance-covariance matrices of item parameter estimatescovirt
Dichotomous Response Model (DRM) Probabilitiesdrm
Item parameter estimation using MMLE-EM algorithmest_irt
Fixed ability parameter calibrationest_item
Multiple-group item calibration using MMLE-EM algorithmest_mg
Estimate examinees' ability (proficiency) parametersest_score est_score.default est_score.est_irt
Generate Weightsgen.weight
Extract various elements from 'est_irt', 'est_mg', and 'est_item' objectsgetirt getirt.est_irt getirt.est_item getirt.est_mg
Generalized IRT residual-based DIF detection framework for multiple groups (GRDIF)grdif grdif.default grdif.est_irt grdif.est_item
Item and Test Information Functioninfo info.default info.est_irt info.est_item
Traditional IRT item fit statisticsirtfit irtfit.default irtfit.est_irt irtfit.est_item
Loglikelihood of Ability Parametersllike_score
LSAT6 dataLSAT6
Lord-Wingersky Recursion Formulalwrc
Pseudo-count D2 methodpcd2
Plot Item and Test Information Functionsplot.info
Draw raw and standardized residual plotsplot.irtfit
Plot ICC and TCCplot.traceline
Polytomous Response Model (PRM) Probabilities (GRM and GPCM)prm
IRT residual-based differential item functioning (RDIF) detection frameworkrdif rdif.default rdif.est_irt rdif.est_item
Recursion-based MST evaluation methodreval_mst
Run flexMIRT through Rrun_flexmirt
Create a data frame of item metadatashape_df
Simulated single-item format CAT DatasimCAT_DC
Simulated mixed-item format CAT DatasimCAT_MX
Simulated Response Datasimdat
Simulated multiple-group datasimMG
Simulated 1-3-3 MST panel datasimMST
Summary of item calibrationsummary summary.est_irt summary.est_item summary.est_mg
S-X2 fit statisticsx2_fit sx2_fit.default sx2_fit.est_irt sx2_fit.est_item
Compute Item/Test Characteristic Functionstraceline traceline.default traceline.est_irt traceline.est_item
Write a "-prm.txt" file for flexMIRTwrite.flexmirt