Package: measr 1.0.0.9000

measr: Bayesian Psychometric Measurement Using 'Stan'

Estimate diagnostic classification models (also called cognitive diagnostic models) with 'Stan'. Diagnostic classification models are confirmatory latent class models, as described by Rupp et al. (2010, ISBN: 978-1-60623-527-0). Automatically generate 'Stan' code for the general loglinear cognitive diagnostic diagnostic model proposed by Henson et al. (2009) <doi:10.1007/s11336-008-9089-5> and other subtypes that introduce additional model constraints. Using the generated 'Stan' code, estimate the model evaluate the model's performance using model fit indices, information criteria, and reliability metrics.

Authors:W. Jake Thompson [aut, cre], Nathan Jones [ctb], Matthew Johnson [cph], Paul-Christian Bürkner [cph], University of Kansas [cph], Institute of Education Sciences [fnd]

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measr.pdf |measr.html✨
measr/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/wjakethompson/measr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • ecpe_data - Examination for the Certificate of Proficiency in English
  • ecpe_qmatrix - Examination for the Certificate of Proficiency in English
  • mdm_data - MacReady & Dayton (1977) Multiplication Data
  • mdm_qmatrix - MacReady & Dayton (1977) Multiplication Data

On CRAN:

bayesiancdmcmdstanrcognitive-diagnosiscognitive-diagnostic-modelsdcmdiagnostic-classification-modelspsychometricsrstanstan

44 exports 8 stars 2.05 score 70 dependencies 28 scripts 1.1k downloads

Last updated 1 months agofrom:bacc0a799b. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 11 2024
R-4.5-win-x86_64NOTESep 11 2024
R-4.5-linux-x86_64NOTESep 11 2024
R-4.4-win-x86_64NOTESep 11 2024
R-4.4-mac-x86_64NOTESep 11 2024
R-4.4-mac-aarch64NOTESep 11 2024
R-4.3-win-x86_64NOTESep 11 2024
R-4.3-mac-x86_64NOTESep 11 2024
R-4.3-mac-aarch64NOTESep 11 2024

Exports::=.data%>%add_criterionadd_fitadd_reliabilityadd_respondent_estimatesas_drawsas_labelas_measrfitas_namecreate_profilesdefault_dcm_priorsEenquoenquosfit_m2fit_ppmcget_parametersis_measrfitis_measrpriorloglik_arraylooloo_comparemeasr_dcmmeasr_examplesmeasr_extractmeasrfitmeasrpriorPrpriorprior_prior_stringreliabilityrvar_madrvar_maxrvar_meanrvar_medianrvar_minrvar_prodrvar_sdrvar_sumrvar_varwaic

Dependencies:abindbackportsBHbroomcallrcheckmateclicolorspacecpp11data.tabledcm2descdistributionaldplyrdtplyrfansifarverfsgenericsggplot2glueGPArotationgridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmnormtmodelrmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpspsychpurrrQuickJSRR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Getting started with measr

Rendered frommeasr.Rmdusingknitr::rmarkdownon Sep 11 2024.

Last update: 2024-01-08
Started: 2023-03-23

measr: Bayesian psychometric measurement using Stan

W. Jake Thompson

Rendered frompaper.Rmdusingknitr::rmarkdownon Sep 11 2024.

Last update: 2023-12-22
Started: 2023-11-06

Readme and manuals

Help Manual

Help pageTopics
Coerce objects to a 'measrfit'as_measrfit as_measrfit.default
Combine multiple measrprior objects into one measrpriorc.measrprior
Generate mastery profilescreate_profiles
Default priors for diagnostic classification modelsdefault_dcm_priors
Examination for the Certificate of Proficiency in English (ECPE)ecpe_data ecpe_qmatrix
Estimate the M_2 fit statistic for diagnostic classification modelsfit_m2.measrdcm
Posterior predictive model checks for assessing model fitfit_ppmc
Get a list of possible parametersget_parameters
Check if argument is a 'measrfit' objectis_measrfit
Checks if argument is a 'measrprior' objectis_measrprior
Extract the log-likelihood of an estimated modelloglik_array loglik_array.measrdcm
Relative model fit comparisonsloo_compare.measrfit
Efficient approximate leave-one-out cross-validation (LOO)loo.measrfit
MacReady & Dayton (1977) Multiplication Datamdm_data mdm_qmatrix
Fit Bayesian diagnostic classification modelsmeasr_dcm
Determine if code is executed interactively or in pkgdownmeasr_examples
Extract components of a 'measrfit' object.measr_extract measr_extract.measrdcm
Create a 'measrfit' objectmeasrfit
Class 'measrfit' of models fitted with the *measr* packagemeasrfit-class
Prior definitions for *measr* modelsmeasrprior prior prior_ prior_string
Add model evaluation metrics model objectsadd_criterion add_fit add_reliability add_respondent_estimates model_evaluation
Posterior draws of respondent proficiencypredict.measrdcm
Estimate the reliability of psychometric modelsreliability reliability.measrdcm
Widely applicable information criterion (WAIC)waic.measrfit