Package: exametrika 1.14.0

exametrika: Test Theory Analysis and Biclustering
Implements comprehensive test data engineering methods as described in Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for engineering and processing test data: Classical Test Theory (CTT) with reliability coefficients for continuous ability assessment; Item Response Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank Analysis (LRA) for ordinal clustering with automatic determination of cluster numbers; Biclustering methods including infinite relational models for simultaneous clustering of examinees and items without predefined cluster numbers; and Bayesian Network Models (BNM) for visualizing inter-item dependencies. Features local dependence analysis through LRA and biclustering, parameter estimation, dimensionality assessment, and network structure visualization for educational, psychological, and social science research.
Authors:
exametrika_1.14.0.tar.gz
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exametrika_1.14.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
exametrika/json (API)
NEWS
| # Install 'exametrika' in R: |
| install.packages('exametrika', repos = c('https://kosugitti.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kosugitti/exametrika/issues
Pkgdown/docs site:https://kosugitti.github.io
Last updated from:66cfe9f9ef. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 216 | ||
| linux-devel-x86_64 | OK | 239 | ||
| source / vignettes | OK | 273 | ||
| linux-release-arm64 | OK | 215 | ||
| linux-release-x86_64 | OK | 195 | ||
| macos-release-arm64 | OK | 215 | ||
| macos-release-x86_64 | OK | 297 | ||
| macos-oldrel-arm64 | OK | 174 | ||
| macos-oldrel-x86_64 | OK | 300 | ||
| windows-devel | OK | 277 | ||
| windows-release | OK | 279 | ||
| windows-oldrel | OK | 278 | ||
| wasm-release | OK | 121 |
Exports:AlphaCoefficientBiclusteringBiclustering_IRMBINETBiserialCorrelationBNMBNM_GABNM_PBILcalcFitIndicesCCRRchatterjee_matrixchatterjee_xicrrCSRCTTdataFormatDimensionalityDistractorAnalysisGlassoGridSearchGRMgrm_iifgrm_probIIF2PLMIIF3PLMInterItemAnalysisIRMIRTITBiserialItemEntropyItemFitItemInformationFuncItemLiftItemOddsItemReportItemStatisticsItemThresholdItemTotalCorrJCRRJointSampleSizeJSRLCALDBLDLRALDLRA_PBILLogisticModellongdataFormatLRAMutualInformationnrsOmegaCoefficientpassagepercentilePhiCoefficientpolychoricPolychoricCorrelationMatrixpolyserialRaschModelScoreReportsscorestanineStrLearningGA_BNMStrLearningPBIL_BNMStrLearningPBIL_LDLRAStudentAnalysisTestFitTestFitSaturatedTestInformationFuncTestResponseFuncTestStatisticstetrachoricTetrachoricCorrelationMatrixThreePLMTwoPLMxi_stable
Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixmvtnormpkgconfigRcpprlangvctrs
Bayesian Network and Local Dependence Models
Rendered fromnetwork-models.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-03-19
Started: 2026-02-25
Biclustering and Ranklustering
Rendered frombiclustering.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-04-27
Started: 2026-02-25
exametrika 日本語ガイド
Rendered fromguide-ja.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-03-24
Started: 2026-02-25
Getting Started with exametrika
Rendered fromgetting-started.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-03-24
Started: 2026-02-25
Item Response Theory (IRT)
Rendered fromirt.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-02-25
Started: 2026-02-25
Latent Class and Rank Analysis
Rendered fromlatent-class-rank.Rmdusingknitr::rmarkdownon Jun 02 2026.Last update: 2026-03-19
Started: 2026-02-25
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Alpha Coefficient | AlphaCoefficient |
| Alpha Coefficient if Item removed | AlphaIfDel |
| Prior distribution function with guessing parameter | asymprior |
| Biclustering and Ranklustering Analysis | Biclustering Biclustering.binary Biclustering.default Biclustering.nominal Biclustering.ordinal Biclustering.rated |
| Biclustering with Infinite Relational Model | Biclustering_IRM Biclustering_IRM.binary Biclustering_IRM.default Biclustering_IRM.nominal Biclustering_IRM.ordinal Biclustering_IRM.rated |
| Bicluster Network Model | BINET |
| Biserial Correlation | BiserialCorrelation |
| Binary pattern maker | BitRespPtn |
| Bayesian Network Model | BNM |
| Structure Learning for BNM by simple GA | BNM_GA |
| Structure Learning for BNM by PBIL | BNM_PBIL |
| calc Fit Indices | calcFitIndices |
| Conditional Correct Response Rate | CCRR CCRR.binary CCRR.default CCRR.nominal |
| Pairwise Chatterjee's xi correlation matrix | chatterjee_matrix |
| Chatterjee's xi correlation coefficient | chatterjee_xi |
| Correct Response Rate | crr crr.binary crr.default |
| Conditional Selection Rate | CSR |
| Classical Test Theory | CTT |
| dataFormat | dataFormat |
| Dimensionality | Dimensionality Dimensionality.binary Dimensionality.default Dimensionality.ordinal Dimensionality.rated |
| Distractor Analysis | DistractorAnalysis DistractorAnalysis.LRArated DistractorAnalysis.ratedBiclustering plot.DistractorAnalysis print.DistractorAnalysis |
| Graphical Lasso for Gaussian Graphical Models | Glasso |
| Grid Search for Optimal Parameters | GridSearch |
| Graded Response Model (GRM) | GRM |
| Item Information Function for GRM | grm_iif |
| Probability function for GRM | grm_prob |
| IIF for 2PLM | IIF2PLM |
| IIF for 3PLM | IIF3PLM |
| Inter-Item Analysis for Psychometric Data | InterItemAnalysis |
| IRM (Deprecated) | IRM |
| Estimating Item parameters using EM algorithm | IRT |
| Item-Total Biserial Correlation | ITBiserial ITBiserial.binary ITBiserial.default |
| Item Entropy | ItemEntropy ItemEntropy.binary ItemEntropy.default ItemEntropy.ordinal |
| Model Fit Functions for Items | ItemFit |
| IIF for 4PLM | ItemInformationFunc |
| Item Lift | ItemLift ItemLift.binary ItemLift.default |
| Item Odds | ItemOdds ItemOdds.binary ItemOdds.default |
| Generate Item Report for Non-Binary Test Data | ItemReport |
| Simple Item Statistics | ItemStatistics ItemStatistics.binary ItemStatistics.default ItemStatistics.ordinal |
| Item Threshold | ItemThreshold ItemThreshold.binary ItemThreshold.ordinal |
| Item-Total Correlation | ItemTotalCorr ItemTotalCorr.binary ItemTotalCorr.default ItemTotalCorr.ordinal |
| J12S5000 | J12S5000 |
| J15S3810 | J15S3810 |
| J15S500 | J15S500 |
| J20S400 | J20S400 |
| J20S600 | J20S600 |
| J21S300 | J21S300 |
| J35S500 | J35S500 |
| J35S5000 | J35S5000 |
| J35S515 | J35S515 |
| J50S100 | J50S100 |
| J5S10 | J5S10 |
| J5S1000 | J5S1000 |
| Joint Correct Response Rate | JCRR JCRR.binary JCRR.default JCRR.nominal |
| Joint Sample Size | JointSampleSize JointSampleSize.binary JointSampleSize.default |
| Joint Selection Rate | JSR |
| Latent Class Analysis | LCA |
| LDparam set | LD_param_est |
| Local Dependence Biclustering | LDB |
| Local Dependence Latent Rank Analysis | LDLRA |
| Structure Learning for LDLRA by PBIL algorithm | LDLRA_PBIL |
| Four-Parameter Logistic Model | LogisticModel |
| Long Format Data Conversion | longdataFormat |
| Latent Rank Analysis | LRA LRA.binary LRA.default LRA.ordinal LRA.rated |
| Utility function for searching DAG | maxParents_penalty |
| Mutual Information | MutualInformation MutualInformation.binary MutualInformation.default MutualInformation.ordinal |
| Number Right Score | nrs nrs.binary nrs.default |
| Log-likelihood function used in the Maximization Step (M-Step). | objective_function_IRT |
| Omega Coefficient | OmegaCoefficient |
| Passage Rate of Student | passage passage.binary passage.default |
| Student Percentile Ranks | percentile percentile.binary percentile.default |
| Phi-Coefficient | PhiCoefficient PhiCoefficient.binary PhiCoefficient.default |
| Plot Method for Objects of Class "exametrika" | plot.exametrika |
| Polychoric Correlation | polychoric |
| Polychoric Correlation Matrix | PolychoricCorrelationMatrix PolychoricCorrelationMatrix.default PolychoricCorrelationMatrix.ordinal |
| Polyserial Correlation | polyserial |
| Print Method for Exametrika Objects | print.exametrika |
| internal functions for PSD of Item parameters | PSD_item_params |
| Rasch Model | RaschModel |
| Generate Score Report for Non-Binary Test Data | ScoreReport |
| Prior distribution function with respect to the slope. | slopeprior |
| softmax function | softmax |
| Standardized Score | sscore sscore.binary sscore.default |
| Stanine Scores | stanine stanine.binary stanine.default |
| StrLearningGA_BNM (Deprecated) | StrLearningGA_BNM |
| StrLearningPBIL_BNM (Deprecated) | StrLearningPBIL_BNM |
| StrLearningPBIL_LDLRA (Deprecated) | StrLearningPBIL_LDLRA |
| StudentAnalysis | StudentAnalysis |
| Model Fit Functions for test whole | TestFit |
| Model Fit Functions for saturated model | TestFitSaturated |
| TIF for IRT | TestInformationFunc |
| TRF for IRT | TestResponseFunc |
| Simple Test Statistics | TestStatistics TestStatistics.binary TestStatistics.default TestStatistics.ordinal |
| Tetrachoric Correlation | tetrachoric |
| Tetrachoric Correlation Matrix | TetrachoricCorrelationMatrix TetrachoricCorrelationMatrix.binary TetrachoricCorrelationMatrix.default |
| Three-Parameter Logistic Model | ThreePLM |
| Two-Parameter Logistic Model | TwoPLM |
| Bootstrap-averaged Chatterjee's xi | xi_stable |
