Package: CDM 8.3-7

CDM: Cognitive Diagnosis Modeling

Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. This package enables the estimation of the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>), the multiple group (polytomous) GDINA model (de la Torre, 2011, <doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009, <doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008, <doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992, <doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis (Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>). See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02> or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>) for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as Ravand and Robitzsch (2015).

Authors:Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Ann Cathrice George [aut], Ali Uenlue [aut]

CDM_8.3-7.tar.gz
CDM_8.3-7.zip(r-4.5)CDM_8.3-7.zip(r-4.4)CDM_8.3-7.zip(r-4.3)
CDM_8.3-7.tgz(r-4.4-x86_64)CDM_8.3-7.tgz(r-4.4-arm64)CDM_8.3-7.tgz(r-4.3-x86_64)CDM_8.3-7.tgz(r-4.3-arm64)
CDM_8.3-7.tar.gz(r-4.5-noble)CDM_8.3-7.tar.gz(r-4.4-noble)
CDM_8.3-7.tgz(r-4.4-emscripten)CDM_8.3-7.tgz(r-4.3-emscripten)
CDM.pdf |CDM.html
CDM/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/alexanderrobitzsch/cdm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

cognitive-diagnostic-modelsitem-response-theory

8.66 score 22 stars 28 packages 138 scripts 3.6k downloads 27 mentions 100 exports 7 dependencies

Last updated 6 months agofrom:da0acfeb90. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-win-x86_64OKNov 22 2024
R-4.5-linux-x86_64OKNov 22 2024
R-4.4-win-x86_64OKNov 22 2024
R-4.4-mac-x86_64OKNov 22 2024
R-4.4-mac-aarch64OKNov 22 2024
R-4.3-win-x86_64OKNov 22 2024
R-4.3-mac-x86_64OKNov 22 2024
R-4.3-mac-aarch64OKNov 22 2024

Exports:abs_approxabs_approx_D1cat_pastecdi.klicdm_attach_internal_functioncdm_calc_information_criteriacdm_fa1cdm_fit_normalcdm_matrix1cdm_matrix2cdm_matrixstringcdm_parameter_regularizationcdm_pem_accelerationcdm_pem_acceleration_assign_output_parameterscdm_pem_initscdm_pem_inits_assign_parmlistcdm_penalty_threshold_elnetcdm_penalty_threshold_mcpcdm_penalty_threshold_ridgecdm_penalty_threshold_scadcdm_penalty_threshold_scadL2cdm_penalty_threshold_tlpcdm_penalty_valuescdm_print_summary_callcdm_print_summary_computation_timecdm_print_summary_data_framecdm_print_summary_information_criteriaCDM_rbind_fillCDM_require_namespaceCDM_rmvnormcdm.est.class.accuracycsinkdeltaMethoddindin_identifiabilitydin.deterministicdin.equivalent.classdin.validate.qmatrixdiscrim.indexentropy.lcaequivalent.dinaeval_likelihoodgddgdinagdina.difgdina.waldgdmideal.response.patternIRT_frequencies_defaultIRT_frequencies_wrapperIRT_RMSD_calc_rmsdIRT.anovaIRT.classifyIRT.compareModelsIRT.dataIRT.derivedParametersIRT.expectedCountsIRT.factor.scoresIRT.frequenciesIRT.ICIRT.irfprobIRT.irfprobPlotIRT.itemfitIRT.jackknifeIRT.likelihoodIRT.marginal_posteriorIRT.modelfitIRT.parameterTableIRT.posteriorIRT.predictIRT.repDesignIRT.RMSDIRT.seitem_by_groupitemfit.rmseaitemfit.sx2mcdinamodelfit.cormodelfit.cor.dinmodelfit.cor2numerical_gradientnumerical_Hessiannumerical_Hessian_partialosinkpersonfit.appropriatenessplot_item_masteryreglcasequential.itemssim_modelsim.dinsim.gdinasim.gdina.prepareskill.corskill.polychorskillspace.approximationskillspace.fullskillspace.hierarchyslcasummary_sinkWaldTest

Dependencies:admisclatticeMatrixmvtnormpolycorRcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Cognitive Diagnosis ModelingCDM-package CDM
Likelihood Ratio Test for Model Comparisonsanova.din anova.gdina anova.gdm anova.mcdina anova.reglca anova.slca
Cognitive Diagnostic Indices based on Kullback-Leibler Informationcdi.kli summary.cdi.kli
Utility Functions in 'CDM'abs_approx abs_approx_D1 cat_paste CDM-utilities cdm_attach_internal_function cdm_calc_information_criteria cdm_fa1 cdm_fit_normal cdm_matrix1 cdm_matrix2 cdm_matrixstring cdm_parameter_regularization cdm_pem_acceleration cdm_pem_acceleration_assign_output_parameters cdm_pem_inits cdm_pem_inits_assign_parmlist cdm_penalty_threshold_elnet cdm_penalty_threshold_lasso cdm_penalty_threshold_mcp cdm_penalty_threshold_ridge cdm_penalty_threshold_scad cdm_penalty_threshold_scadL2 cdm_penalty_threshold_tlp cdm_penalty_values cdm_print_summary_call cdm_print_summary_computation_time cdm_print_summary_data_frame cdm_print_summary_information_criteria CDM_rbind_fill CDM_require_namespace CDM_rmvnorm
Classification Reliability in a CDMcdm.est.class.accuracy
Extract Estimated Item Parameters and Skill Class Distribution Parameterscoef.din coef.gdina coef.gdm coef.mcdina coef.slca
Artificial Data: DINA and DINOData-sim sim.dina sim.dino sim.qmatrix
Several Datasets for the 'CDM' Packagedata.cdm data.cdm01 data.cdm02 data.cdm03 data.cdm04 data.cdm05 data.cdm06 data.cdm07 data.cdm08 data.cdm09 data.cdm10
Dataset from Book 'Diagnostic Measurement' of Rupp, Templin and Henson (2010)data.dcm
DTMR Fraction Data (Bradshaw et al., 2014)data.dtmr
Dataset ECPEdata.ecpe
Fraction Subtraction Dataset with Different Subsets of Data and Different Q-Matricesdata.fraction data.fraction1 data.fraction2 data.fraction3 data.fraction4 data.fraction5
Dataset 'data.hr' (Ravand et al., 2013)data.hr
Dataset Jang (2009)data.jang
MELAB Data (Li, 2011)data.melab
Large-Scale Dataset with Multiple Groupsdata.mg
Dataset for Polytomous GDINA Modeldata.pgdina
PISA 2000 Reading Study (Chen & de la Torre, 2014)data.pisa00R.cc data.pisa00R.ct
Dataset SDA6 (Jurich & Bradshaw, 2014)data.sda6
Dataset Student Questionnairedata.Students
TIMSS 2003 Mathematics 8th Grade (Su et al., 2013)data.timss03.G8.su
TIMSS 2007 Mathematics 4th Grade (Lee et al., 2011)data.timss07.G4.lee data.timss07.G4.py data.timss07.G4.Qdomains
TIMSS 2011 Mathematics 4th Grade Austrian Studentsdata.timss11.G4.AUT data.timss11.G4.AUT.part data.timss11.G4.sa
Variance Matrix of a Nonlinear Estimator Using the Delta MethoddeltaMethod
Parameter Estimation for Mixed DINA/DINO Modeldin print.din
Identifiability Conditions of the DINA Modeldin_identifiability summary.din_identifiability
Deterministic Classification and Joint Maximum Likelihood Estimation of the Mixed DINA/DINO Modeldin.deterministic
Calculation of Equivalent Skill Classes in the DINA/DINO Modeldin.equivalent.class
Q-Matrix Validation (Q-Matrix Modification) for Mixed DINA/DINO Modeldin.validate.qmatrix
Discrimination Indices at Item-Attribute, Item and Test Leveldiscrim.index discrim.index.din discrim.index.gdina discrim.index.mcdina summary.discrim.index
Test-specific and Item-specific Entropy for Latent Class Modelsentropy.lca summary.entropy.lca
Determination of a Statistically Equivalent DINA Modelequivalent.dina
Evaluation of Likelihoodeval_likelihood prep_data_long_format
Fraction Subtraction Datafraction.subtraction.data
Fraction Subtraction Q-Matrixfraction.subtraction.qmatrix
Generalized Distance Discriminating Methodgdd
Estimating the Generalized DINA (GDINA) Modelgdina plot.gdina print.gdina summary.gdina
Differential Item Functioning in the GDINA Modelgdina.dif summary.gdina.dif
Wald Statistic for Item Fit of the DINA and ACDM Rule for GDINA Modelgdina.wald summary.gdina.wald
General Diagnostic Modelgdm plot.gdm print.gdm summary.gdm
Ideal Response Patternideal.response.pattern
Helper Function for Conducting Likelihood Ratio TestsIRT.anova
Individual Classification for Fitted ModelsIRT.classify
Comparisons of Several ModelsIRT.compareModels summary.IRT.compareModels
S3 Method for Extracting Used Item Response DatasetIRT.data IRT.data.din IRT.data.gdina IRT.data.gdm IRT.data.mcdina IRT.data.reglca IRT.data.slca
S3 Method for Extracting Expected CountsIRT.expectedCounts IRT.expectedCounts.din IRT.expectedCounts.gdina IRT.expectedCounts.gdm IRT.expectedCounts.mcdina IRT.expectedCounts.reglca IRT.expectedCounts.slca
S3 Methods for Extracting Factor Scores (Person Classifications)IRT.factor.scores IRT.factor.scores.din IRT.factor.scores.gdina IRT.factor.scores.gdm IRT.factor.scores.mcdina IRT.factor.scores.slca
S3 Method for Computing Observed and Expected Frequencies of Univariate and Bivariate MarginalsIRT.frequencies IRT.frequencies.din IRT.frequencies.gdina IRT.frequencies.gdm IRT.frequencies.mcdina IRT.frequencies.slca IRT_frequencies_default IRT_frequencies_wrapper
Information CriteriaIRT.IC
S3 Methods for Extracting Item Response FunctionsIRT.irfprob IRT.irfprob.din IRT.irfprob.gdina IRT.irfprob.gdm IRT.irfprob.mcdina IRT.irfprob.reglca IRT.irfprob.slca
Plot Item Response FunctionsIRT.irfprobPlot
S3 Methods for Computing Item FitIRT.itemfit IRT.itemfit.din IRT.itemfit.gdina IRT.itemfit.gdm IRT.itemfit.reglca IRT.itemfit.slca
Jackknifing an Item Response Modelcoef.IRT.jackknife IRT.derivedParameters IRT.jackknife IRT.jackknife.gdina vcov.IRT.jackknife
S3 Methods for Extracting of the Individual Likelihood and the Individual PosteriorIRT.likelihood IRT.likelihood.din IRT.likelihood.gdina IRT.likelihood.gdm IRT.likelihood.mcdina IRT.likelihood.reglca IRT.likelihood.slca IRT.posterior IRT.posterior.din IRT.posterior.gdina IRT.posterior.gdm IRT.posterior.mcdina IRT.posterior.reglca IRT.posterior.slca
S3 Method for Computation of Marginal Posterior DistributionIRT.marginal_posterior IRT.marginal_posterior.din IRT.marginal_posterior.gdina IRT.marginal_posterior.mcdina
S3 Methods for Assessing Model FitIRT.modelfit IRT.modelfit.din IRT.modelfit.gdina summary.IRT.modelfit.din summary.IRT.modelfit.gdina
S3 Method for Extracting a Parameter TableIRT.parameterTable
Generation of a Replicate Design for 'IRT.jackknife'IRT.repDesign
Root Mean Square Deviation (RMSD) Item Fit StatisticIRT.RMSD IRT_RMSD_calc_rmsd summary.IRT.RMSD
Create Dataset with Group-Specific Itemsitem_by_group
RMSEA Item Fititemfit.rmsea
S-X2 Item Fit Statistic for Dichotomous Dataitemfit.sx2 plot.itemfit.sx2 summary.itemfit.sx2
Extract Log-LikelihoodlogLik.din logLik.gdina logLik.gdm logLik.mcdina logLik.reglca logLik.slca
Multiple Choice DINA Modelmcdina print.mcdina summary.mcdina
Assessing Model Fit and Local Dependence by Comparing Observed and Expected Item Pair Correlationsmodelfit.cor modelfit.cor.din modelfit.cor2 summary.modelfit.cor.din
Numerical Computation of the Hessian Matrixnumerical_gradient numerical_Hessian numerical_Hessian_partial
Opens and Closes a 'sink' Connectioncsink osink
Appropriateness Statistic for Person Fit Assessmentpersonfit.appropriateness plot.personfit.appropriateness summary.personfit.appropriateness
S3 Methods for Plotting Item Probabilitiesplot_item_mastery plot_item_mastery.din plot_item_mastery.gdina
Plot Method for Objects of Class dinplot.din
Expected Values and Predicted Probabilities from Item Response Response ModelsIRT.predict predict.din predict.gdina predict.gdm predict.mcdina predict.slca
Print Method for Objects of Class summary.dinprint.summary.din
Regularized Latent Class Analysisreglca summary.reglca
Constructing a Dataset with Sequential Pseudo Items for Ordered Item Responsessequential.items
Simulate an Item Response Modelsim_model
Data Simulation Tool for DINA, DINO and mixed DINA and DINO Datasim.din
Simulation of the GDINA modelsim.gdina sim.gdina.prepare
Tetrachoric or Polychoric Correlations between Attributesskill.cor skill.polychor
Skill Space Approximationskillspace.approximation
Creation of a Hierarchical Skill Spaceskillspace.full skillspace.hierarchy
Structured Latent Class Analysis (SLCA)plot.slca print.slca slca summary.slca
Prints 'summary' and 'sink' Output in a Filesummary_sink
Summary Method for Objects of Class dinsummary.din
Asymptotic Covariance Matrix, Standard Errors and Confidence Intervalsconfint.din IRT.se IRT.se.din vcov.din
Wald Test for a Linear HypothesisWaldTest