Package: exametrika 1.15.0

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:Koji Kosugi [aut, cre]

exametrika_1.15.0.tar.gz
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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
exametrika/json (API)

# 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

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

On CRAN:

Conda:

cpp

7.89 score 5 stars 199 scripts 629 downloads 75 exports 13 dependencies

Last updated from:f8bc4ea57f. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK249
linux-devel-x86_64OK227
source / vignettesOK261
linux-release-arm64OK234
linux-release-x86_64OK222
macos-release-arm64OK142
macos-release-x86_64OK368
macos-oldrel-arm64OK130
macos-oldrel-x86_64OK355
windows-develOK256
windows-releaseOK291
windows-oldrelOK256
wasm-releaseOK165

Exports:AlphaCoefficientBiclusteringBiclustering_IRMBINETBiserialCorrelationBNMBNM_GABNM_PBILcalcFitIndicesCCRRchatterjee_matrixchatterjee_xicrrCSRCTTdataFormatDimensionalityDistractorAnalysisGlassoGridSearchGRMgrm_iifgrm_probIIF2PLMIIF3PLMInterItemAnalysisIRMIRTITBiserialItemEntropyItemFitItemInformationFuncItemLiftItemOddsItemReportItemStatisticsItemThresholdItemTotalCorrJCRRJointSampleSizeJSRLCALDBLDLRALDLRA_PBILLogisticModellongdataFormatLRAMutualInformationnrsOmegaCoefficientpassagepercentilePhiCoefficientpolychoricPolychoricCorrelationMatrixpolyserialRaschModelScoreReportsscorestanineStrLearningGA_BNMStrLearningPBIL_BNMStrLearningPBIL_LDLRAStudentAnalysisTestFitTestFitSaturatedTestInformationFuncTestResponseFuncTestStatisticstetrachoricTetrachoricCorrelationMatrixThreePLMTwoPLMxi_stable

Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixmvtnormpkgconfigRcpprlangvctrs

Biclustering and Ranklustering
Biclustering | Ranklustering | Finding Optimal Number of Classes and Fields | Grid Search | Infinite Relational Model (IRM) | Biclustering for Polytomous Data | Ordinal Data | Nominal Data | Rated Data (Multiple-Choice with Correct Answers) | Rated IRM | Distractor Analysis | Reference

Last update: 2026-04-27
Started: 2026-02-25

exametrika 日本語ガイド
概要 | 機能 | 古典的手法 | 潜在構造分析 | モデルの概要 | 局所依存モデル | モデル選択ガイド | インストール | 依存パッケージ | データ形式と使用方法 | 基本的な使用方法 | データ要件 | データフォーマット | サンプルデータセット | 使用例 | テスト統計量 | 項目統計量 | CTT | IRT | GRM | LCA | LRA | LRA 順序尺度データへの適用 | LRA 名義尺度データへの適用 | バイクラスタリング | グリッドサーチ | 無限関係モデル | 多段階反応データ用のバイクラスタリング | 順序尺度データ | 名義尺度データ | ベイジアンネットワークモデル | 遺伝的アルゴリズムによる構造学習 | PBILによる構造学習 | 局所依存潜在ランク分析 | 局所依存バイクラスタリング | バイクラスターネットワークモデル | 参考文献

Last update: 2026-03-24
Started: 2026-02-25

Getting Started with exametrika
Overview | Installation | Data Format | Data Requirements | Data Formatting | Sample Datasets | Basic Statistics | Test Statistics | Item Statistics | Classical Test Theory | Next Steps | Reference

Last update: 2026-03-24
Started: 2026-02-25

Bayesian Network and Local Dependence Models
Bayesian Network Model (BNM) | Creating the Graph | Running BNM | Structure Learning with Genetic Algorithm | Structure Learning with PBIL | Local Dependence Latent Rank Analysis (LDLRA) | Setting Up Rank-Specific Graphs | Running LDLRA | Structure Learning for LDLRA with PBIL | Local Dependence Biclustering (LDB) | Bicluster Network Model (BINET) | Model Comparison | Reference

Last update: 2026-03-19
Started: 2026-02-25

Latent Class and Rank Analysis
Latent Class Analysis (LCA) | LCA Plot Types | Latent Rank Analysis (LRA) | LRA for Ordinal Data | LRA for Rated/Nominal Data | Reference

Last update: 2026-03-19
Started: 2026-02-25

Item Response Theory (IRT)
IRT for Binary Data | Plot Types | GRM: Graded Response Model | References

Last update: 2026-02-25
Started: 2026-02-25

Readme and manuals

Help Manual

Help pageTopics
Alpha CoefficientAlphaCoefficient
Alpha Coefficient if Item removedAlphaIfDel
Prior distribution function with guessing parameterasymprior
Biclustering and Ranklustering AnalysisBiclustering Biclustering.binary Biclustering.default Biclustering.nominal Biclustering.ordinal Biclustering.rated
Biclustering with Infinite Relational ModelBiclustering_IRM Biclustering_IRM.binary Biclustering_IRM.default Biclustering_IRM.nominal Biclustering_IRM.ordinal Biclustering_IRM.rated
Bicluster Network ModelBINET
Biserial CorrelationBiserialCorrelation
Binary pattern makerBitRespPtn
Bayesian Network ModelBNM
Structure Learning for BNM by simple GABNM_GA
Structure Learning for BNM by PBILBNM_PBIL
calc Fit IndicescalcFitIndices
Conditional Correct Response RateCCRR CCRR.binary CCRR.default CCRR.nominal
Pairwise Chatterjee's xi correlation matrixchatterjee_matrix
Chatterjee's xi correlation coefficientchatterjee_xi
Correct Response Ratecrr crr.binary crr.default
Conditional Selection RateCSR
Classical Test TheoryCTT
dataFormatdataFormat
DimensionalityDimensionality Dimensionality.binary Dimensionality.default Dimensionality.ordinal Dimensionality.rated
Distractor AnalysisDistractorAnalysis DistractorAnalysis.LRArated DistractorAnalysis.ratedBiclustering plot.DistractorAnalysis print.DistractorAnalysis
Graphical Lasso for Gaussian Graphical ModelsGlasso
Grid Search for Optimal ParametersGridSearch
Graded Response Model (GRM)GRM
Item Information Function for GRMgrm_iif
Probability function for GRMgrm_prob
IIF for 2PLMIIF2PLM
IIF for 3PLMIIF3PLM
Inter-Item Analysis for Psychometric DataInterItemAnalysis
IRM (Deprecated)IRM
Estimating Item parameters using EM algorithmIRT
Item-Total Biserial CorrelationITBiserial ITBiserial.binary ITBiserial.default
Item EntropyItemEntropy ItemEntropy.binary ItemEntropy.default ItemEntropy.ordinal
Model Fit Functions for ItemsItemFit
IIF for 4PLMItemInformationFunc
Item LiftItemLift ItemLift.binary ItemLift.default
Item OddsItemOdds ItemOdds.binary ItemOdds.default
Generate Item Report for Non-Binary Test DataItemReport
Simple Item StatisticsItemStatistics ItemStatistics.binary ItemStatistics.default ItemStatistics.ordinal
Item ThresholdItemThreshold ItemThreshold.binary ItemThreshold.ordinal
Item-Total CorrelationItemTotalCorr ItemTotalCorr.binary ItemTotalCorr.default ItemTotalCorr.ordinal
J12S5000J12S5000
J15S3810J15S3810
J15S500J15S500
J20S400J20S400
J20S600J20S600
J21S300J21S300
J35S500J35S500
J35S5000J35S5000
J35S515J35S515
J50S100J50S100
J5S10J5S10
J5S1000J5S1000
Joint Correct Response RateJCRR JCRR.binary JCRR.default JCRR.nominal
Joint Sample SizeJointSampleSize JointSampleSize.binary JointSampleSize.default
Joint Selection RateJSR
Latent Class AnalysisLCA
LDparam setLD_param_est
Local Dependence BiclusteringLDB
Local Dependence Latent Rank AnalysisLDLRA
Structure Learning for LDLRA by PBIL algorithmLDLRA_PBIL
Four-Parameter Logistic ModelLogisticModel
Long Format Data ConversionlongdataFormat
Latent Rank AnalysisLRA LRA.binary LRA.default LRA.ordinal LRA.rated
Utility function for searching DAGmaxParents_penalty
Mutual InformationMutualInformation MutualInformation.binary MutualInformation.default MutualInformation.ordinal
Number Right Scorenrs nrs.binary nrs.default
Log-likelihood function used in the Maximization Step (M-Step).objective_function_IRT
Omega CoefficientOmegaCoefficient
Passage Rate of Studentpassage passage.binary passage.default
Student Percentile Rankspercentile percentile.binary percentile.default
Phi-CoefficientPhiCoefficient PhiCoefficient.binary PhiCoefficient.default
Plot Method for Objects of Class "exametrika"plot.exametrika
Polychoric Correlationpolychoric
Polychoric Correlation MatrixPolychoricCorrelationMatrix PolychoricCorrelationMatrix.default PolychoricCorrelationMatrix.ordinal
Polyserial Correlationpolyserial
Print Method for Exametrika Objectsprint.exametrika
internal functions for PSD of Item parametersPSD_item_params
Rasch ModelRaschModel
Generate Score Report for Non-Binary Test DataScoreReport
Prior distribution function with respect to the slope.slopeprior
softmax functionsoftmax
Standardized Scoresscore sscore.binary sscore.default
Stanine Scoresstanine stanine.binary stanine.default
StrLearningGA_BNM (Deprecated)StrLearningGA_BNM
StrLearningPBIL_BNM (Deprecated)StrLearningPBIL_BNM
StrLearningPBIL_LDLRA (Deprecated)StrLearningPBIL_LDLRA
StudentAnalysisStudentAnalysis
Model Fit Functions for test wholeTestFit
Model Fit Functions for saturated modelTestFitSaturated
TIF for IRTTestInformationFunc
TRF for IRTTestResponseFunc
Simple Test StatisticsTestStatistics TestStatistics.binary TestStatistics.default TestStatistics.ordinal
Tetrachoric Correlationtetrachoric
Tetrachoric Correlation MatrixTetrachoricCorrelationMatrix TetrachoricCorrelationMatrix.binary TetrachoricCorrelationMatrix.default
Three-Parameter Logistic ModelThreePLM
Two-Parameter Logistic ModelTwoPLM
Bootstrap-averaged Chatterjee's xixi_stable