Package: mirt 1.43

Phil Chalmers

mirt: Multidimensional Item Response Theory

Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported.

Authors:Phil Chalmers [aut, cre], Joshua Pritikin [ctb], Alexander Robitzsch [ctb], Mateusz Zoltak [ctb], KwonHyun Kim [ctb], Carl F. Falk [ctb], Adam Meade [ctb], Lennart Schneider [ctb], David King [ctb], Chen-Wei Liu [ctb], Ogreden Oguzhan [ctb]

mirt_1.43.tar.gz
mirt_1.43.tar.gz(r-4.5-noble)mirt_1.43.tar.gz(r-4.4-noble)
mirt_1.43.tgz(r-4.4-emscripten)mirt_1.43.tgz(r-4.3-emscripten)
mirt.pdf |mirt.html✨
mirt/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/philchalmers/mirt/issues

Pkgdown site:https://philchalmers.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • ASVAB - Description of ASVAB data
  • Bock1997 - Description of Bock 1997 data
  • LSAT6 - Description of LSAT6 data
  • LSAT7 - Description of LSAT7 data
  • SAT12 - Description of SAT12 data
  • SLF - Social Life Feelings Data
  • Science - Description of Science data
  • deAyala - Description of deAyala data

openblascppopenmp

9.12 score 1 stars 38 packages 1.4k scripts 8.2k downloads 81 mentions 70 exports 66 dependencies

Last updated 2 months agofrom:b944e4679f. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 25 2024
R-4.5-linux-x86_64OKDec 25 2024

Exports:anovaareainfoaverageMIbfactorboot.LRboot.mirtcoefcreateGroupcreateItemDIFdraw_parametersDRFDTFempirical_ESempirical_plotempirical_rxxestfun.AllModelClassexpand.tableexpected.itemexpected.testextract.groupextract.itemextract.mirtfixedCalibfixeffscoresgen.difficultyimputeMissingitemfititemGAMiteminfoitemplotitemstatskey2binarylagrangelikert2intlogLikM2marginal_rxxMDIFFmdirtMDISCmirtmirt.modelmirtClustermixedmirtmod2valuesmultipleGroupnumerical_derivpersonfitPLCI.mirtplotpoly2dichprobtracerandefRCIread.mirtremap.distanceresidualsreverse.scoreRMSD_DIFsecondOrderTestSIBTESTsimdatasummarytestinfothetaCombtraditional2mirtvcovwald

Dependencies:audiobeeprbriocallrcliclustercodetoolscrayoncurldcurverDerivdescdiffobjdigestdplyrevaluatefansifsfuturefuture.applygenericsglobalsglueGPArotationgridExtragtablejsonlitelatticelifecyclelistenvmagrittrMASSMatrixmgcvnlmeparallellypbapplypermutepillarpkgbuildpkgconfigpkgloadpraiseprocessxprogressrpsR.methodsS3R.ooR.utilsR6RcppRcppArmadillorlangrprojrootRPushbulletsessioninfoSimDesignsnowtestthattibbletidyselectutf8vctrsveganwaldowithr

Online Vignettes

Rendered frommirt-vignettes.Rmdusingknitr::knitron Dec 25 2024.

Last update: 2015-01-22
Started: 2014-06-22

Readme and manuals

Help Manual

Help pageTopics
Full information maximum likelihood estimation of IRT models.mirt-package
Compare nested models with likelihood-based statisticsanova,DiscreteClass-method anova,MixedClass-method anova,MixtureClass-method anova,MultipleGroupClass-method anova,SingleGroupClass-method anova-method
Function to calculate the area under a selection of information curvesareainfo
Description of ASVAB dataASVAB
Collapse values from multiple imputation drawsaverageMI
Full-Information Item Bi-factor and Two-Tier Analysisbfactor
Description of Bock 1997 dataBock1997
Parametric bootstrap likelihood-ratio testboot.LR
Calculate bootstrapped standard errors for estimated modelsboot.mirt
Extract raw coefs from model objectcoef,DiscreteClass-method coef,MixedClass-method coef,MixtureClass-method coef,MultipleGroupClass-method coef,SingleGroupClass-method coef-method
Create a user defined group-level object with correct generic functionscreateGroup
Create a user defined item with correct generic functionscreateItem
Description of deAyala datadeAyala
Differential item functioning statisticsDIF
Class "DiscreteClass"DiscreteClass-class
Draw plausible parameter instantiations from a given modeldraw_parameters
Differential Response Functioning statisticsDRF
Differential test functioning statisticsDTF
Empirical effect sizes based on latent trait estimatesempirical_ES
Function to generate empirical unidimensional item and test plotsempirical_plot
Function to calculate the empirical (marginal) reliabilityempirical_rxx
Extract Empirical Estimating Functionsestfun.AllModelClass
Expand summary table of patterns and frequenciesexpand.table
Function to calculate expected value of itemexpected.item
Function to calculate expected test scoreexpected.test
Extract a group from a multiple group mirt objectextract.group
Extract an item object from mirt objectsextract.item
Extract various elements from estimated model objectsextract.mirt
Fixed-item calibration methodfixedCalib
Compute latent regression fixed effect expected valuesfixef
Compute factor score estimates (a.k.a, ability estimates, latent trait estimates, etc)fscores
Generalized item difficulty summariesgen.difficulty
Imputing plausible data for missing valuesimputeMissing
Item fit statisticsitemfit
Parametric smoothed regression lines for item response probability functionsitemGAM plot.itemGAM
Function to calculate item informationiteminfo
Displays item surface and information plotsitemplot
Generic item summary statisticsitemstats
Score a test by converting response patterns to binary datakey2binary
Lagrange test for freeing parameterslagrange
Convert ordered Likert-scale responses (character or factors) to integerslikert2int
Extract log-likelihoodlogLik,DiscreteClass-method logLik,MixedClass-method logLik,MixtureClass-method logLik,MultipleGroupClass-method logLik,SingleGroupClass-method logLik-method
Description of LSAT6 dataLSAT6
Description of LSAT7 dataLSAT7
Compute the M2 model fit statisticM2
Function to calculate the marginal reliabilitymarginal_rxx
Compute multidimensional difficulty indexMDIFF
Multidimensional discrete item response theorymdirt
Compute multidimensional discrimination indexMDISC
Full-Information Item Factor Analysis (Multidimensional Item Response Theory)mirt
Specify model informationmirt.model
Define a parallel cluster object to be used in internal functionsmirtCluster
Class "MixedClass"MixedClass-class
Mixed effects modeling for MIRT modelsmixedmirt
Class "MixtureClass"MixtureClass-class
Convert an estimated mirt model to a data.framemod2values
Multiple Group EstimationmultipleGroup
Class "MultipleGroupClass"MultipleGroupClass-class
Compute numerical derivativesnumerical_deriv
Person fit statisticspersonfit
Compute profiled-likelihood (or posterior) confidence intervalsPLCI.mirt
Plot various test-implied functions from modelsplot,DiscreteClass,missing-method plot,MixtureClass,missing-method plot,MultipleGroupClass,missing-method plot,MultipleGroupClass-method plot,SingleGroupClass,missing-method plot,SingleGroupClass-method plot-method
Change polytomous items to dichotomous item formatpoly2dich
Print the model objectsprint,DiscreteClass-method print,MixedClass-method print,MixtureClass-method print,MultipleGroupClass-method print,SingleGroupClass-method print-method
Print generic for customized data.frame console outputprint.mirt_df
Print generic for customized list console outputprint.mirt_list
Print generic for customized matrix console outputprint.mirt_matrix
Function to calculate probability trace linesprobtrace
Compute posterior estimates of random effectrandef
Model-based Reliable Change IndexRCI
Translate mirt parameters into suitable structure for plink packageread.mirt
Remap item categories to have integer distances of 1remap.distance
Compute model residualsresiduals,DiscreteClass-method residuals,MixtureClass-method residuals,MultipleGroupClass-method residuals,SingleGroupClass-method residuals-method
Reverse score one or more items from a response matrixreverse.score
RMSD effect size statistic to quantify category-level DIFRMSD_DIF
Description of SAT12 dataSAT12
Description of Science dataScience
Second-order test of convergencesecondOrderTest
Show model objectshow,DiscreteClass-method show,MixedClass-method show,MixtureClass-method show,MultipleGroupClass-method show,SingleGroupClass-method show-method
(Generalized) Simultaneous Item Bias Test (SIBTEST)SIBTEST
Simulate response patternssimdata
Class "SingleGroupClass"SingleGroupClass-class
Social Life Feelings DataSLF
Summary of model objectsummary,DiscreteClass-method summary,MixedClass-method summary,MixtureClass-method summary,MultipleGroupClass-method summary,SingleGroupClass-method summary-method
Function to calculate test informationtestinfo
Create all possible combinations of vector inputthetaComb
Convert traditional IRT metric into slope-intercept form used in mirttraditional2mirt
Extract parameter variance covariance matrixvcov,DiscreteClass-method vcov,MixedClass-method vcov,MixtureClass-method vcov,MultipleGroupClass-method vcov,SingleGroupClass-method vcov-method
Wald statistics for mirt modelswald