{ "_id": "6a1eb538b25058d4daadd92d", "Package": "exametrika", "Type": "Package", "Title": "Test Theory Analysis and Biclustering", "Version": "1.14.0", "Authors@R": "person(\"Koji Kosugi\", , , \"kosugitti@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-5816-0099\"))", "Description": "Implements comprehensive test data engineering methods as\ndescribed in Shojima (2022, ISBN:978-9811699856). Provides\nstatistical techniques for engineering and processing test\ndata: Classical Test Theory (CTT) with reliability coefficients\nfor continuous ability assessment; Item Response Theory (IRT)\nincluding Rasch, 2PL, and 3PL models with item/test information\nfunctions; Latent Class Analysis (LCA) for nominal clustering;\nLatent Rank Analysis (LRA) for ordinal clustering with\nautomatic determination of cluster numbers; Biclustering\nmethods including infinite relational models for simultaneous\nclustering of examinees and items without predefined cluster\nnumbers; and Bayesian Network Models (BNM) for visualizing\ninter-item dependencies. Features local dependence analysis\nthrough LRA and biclustering, parameter estimation,\ndimensionality assessment, and network structure visualization\nfor educational, psychological, and social science research.", "License": "MIT + file LICENSE", "Language": "en-US", "Encoding": "UTF-8", "LazyData": "true", "BuildVignettes": "true", "URL": "https://kosugitti.github.io/exametrika/,\nhttps://github.com/kosugitti/exametrika", "BugReports": "https://github.com/kosugitti/exametrika/issues", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libglpk-dev libxml2-dev", "Repository": "https://kosugitti.r-universe.dev", "Date/Publication": "2026-06-02 08:05:23 UTC", "RemoteUrl": "https://github.com/kosugitti/exametrika", "RemoteRef": "HEAD", "RemoteSha": "66cfe9f9ef97c94740f0eae5f73701ef7b8e5a92", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-02 10:33:01 UTC", "User": "root" }, "Author": "Koji Kosugi [aut, cre] (ORCID: )", "Maintainer": "Koji Kosugi ", "MD5sum": "cf98ea4f383dc5ea53bf8e4b7c08c2dc", "_user": "kosugitti", "_type": "src", "_file": "exametrika_1.14.0.tar.gz", "_fileid": "9519b360f47afc5195797cbe12654e0b94e941ab9a5d3307e545330b4f99c2bc", "_filesize": 4009116, "_sha256": "9519b360f47afc5195797cbe12654e0b94e941ab9a5d3307e545330b4f99c2bc", "_created": "2026-06-02T10:33:01.000Z", "_published": "2026-06-02T10:49:28.794Z", "_distro": "noble", "_jobs": [ { "job": 79051521828, "time": 216, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7355395166" }, { "job": 79051521862, "time": 239, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7355402068" }, { "job": 79051521874, "time": 215, "config": "linux-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7355394778" }, { "job": 79051521893, "time": 195, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7355386734" }, { "job": 79051521988, "time": 174, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7355633109" }, { "job": 79051521843, "time": 300, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "7355424876" }, { "job": 79051521852, "time": 215, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7355590525" }, { "job": 79051521870, "time": 297, "config": "macos-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7355425728" }, { "job": 79050775296, "time": 273, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7355320116" }, { "job": 79051522038, "time": 121, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7355360899" }, { "job": 79051521842, "time": 277, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7355416667" }, { "job": 79051521876, "time": 278, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7355417445" }, { "job": 79051521848, "time": 279, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7355416901" } ], "_buildurl": "https://github.com/r-universe/kosugitti/actions/runs/26813923353", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/kosugitti/exametrika", "_commit": { "id": "66cfe9f9ef97c94740f0eae5f73701ef7b8e5a92", "author": "kosugitti ", "committer": "kosugitti ", "message": "fix: correct user-facing message typos in 4 R files (v1.14.0)\n\nFamily-wide audit of user-visible output strings (plot/message/print/cat)\ntriggered by the `Clusterd` -> `Clustered` rename. 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Infinite Relational Model", "topics": [ "Biclustering_IRM", "Biclustering_IRM.binary", "Biclustering_IRM.default", "Biclustering_IRM.nominal", "Biclustering_IRM.ordinal", "Biclustering_IRM.rated" ] }, { "page": "BINET", "title": "Bicluster Network Model", "topics": [ "BINET" ] }, { "page": "BiserialCorrelation", "title": "Biserial Correlation", "topics": [ "BiserialCorrelation" ] }, { "page": "BitRespPtn", "title": "Binary pattern maker", "topics": [ "BitRespPtn" ] }, { "page": "BNM", "title": "Bayesian Network Model", "topics": [ "BNM" ] }, { "page": "BNM_GA", "title": "Structure Learning for BNM by simple GA", "topics": [ "BNM_GA" ] }, { "page": "BNM_PBIL", "title": "Structure Learning for BNM by PBIL", "topics": [ "BNM_PBIL" ] }, { "page": "calcFitIndices", "title": "calc Fit Indices", "topics": [ "calcFitIndices" ] }, { "page": "CCRR", "title": "Conditional Correct Response Rate", "topics": [ "CCRR", "CCRR.binary", "CCRR.default", "CCRR.nominal" ] }, { "page": "chatterjee_matrix", "title": "Pairwise Chatterjee's xi correlation matrix", "topics": [ "chatterjee_matrix" ] }, { "page": "chatterjee_xi", "title": "Chatterjee's xi correlation coefficient", "topics": [ "chatterjee_xi" ] }, { "page": "crr", "title": "Correct Response Rate", "topics": [ "crr", "crr.binary", "crr.default" ] }, { "page": "CSR", "title": "Conditional Selection Rate", "topics": [ "CSR" ] }, { "page": "CTT", "title": "Classical Test Theory", "topics": [ "CTT" ] }, { "page": "dataFormat", "title": "dataFormat", "topics": [ "dataFormat" ] }, { "page": "Dimensionality", "title": "Dimensionality", "topics": [ "Dimensionality", "Dimensionality.binary", "Dimensionality.default", "Dimensionality.ordinal", "Dimensionality.rated" ] }, { "page": "DistractorAnalysis", "title": "Distractor Analysis", "topics": [ "DistractorAnalysis", "DistractorAnalysis.LRArated", "DistractorAnalysis.ratedBiclustering", "plot.DistractorAnalysis", "print.DistractorAnalysis" ] }, { "page": "Glasso", "title": "Graphical Lasso for Gaussian Graphical Models", "topics": [ "Glasso" ] }, { "page": "GridSearch", "title": "Grid Search for Optimal Parameters", "topics": [ "GridSearch" ] }, { "page": "GRM", "title": "Graded Response Model (GRM)", "topics": [ "GRM" ] }, { "page": "grm_iif", "title": "Item Information Function for GRM", "topics": [ "grm_iif" ] }, { "page": "grm_prob", "title": "Probability function for GRM", "topics": [ "grm_prob" ] }, { "page": "IIF2PLM", "title": "IIF for 2PLM", "topics": [ "IIF2PLM" ] }, { "page": "IIF3PLM", "title": "IIF for 3PLM", "topics": [ "IIF3PLM" ] }, { "page": "InterItemAnalysis", "title": "Inter-Item Analysis for Psychometric Data", "topics": [ "InterItemAnalysis" ] }, { "page": "IRM", "title": "IRM (Deprecated)", "topics": [ "IRM" ] }, { "page": "IRT", "title": "Estimating Item parameters using EM algorithm", "topics": [ "IRT" ] }, { "page": "ITBiserial", "title": "Item-Total Biserial Correlation", "topics": [ "ITBiserial", "ITBiserial.binary", "ITBiserial.default" ] }, { "page": "ItemEntropy", "title": "Item Entropy", "topics": [ "ItemEntropy", "ItemEntropy.binary", "ItemEntropy.default", "ItemEntropy.ordinal" ] }, { "page": "ItemFit", "title": "Model Fit Functions for Items", "topics": [ "ItemFit" ] }, { "page": "ItemInformationFunc", "title": "IIF for 4PLM", "topics": [ "ItemInformationFunc" ] }, { "page": "ItemLift", "title": "Item Lift", "topics": [ "ItemLift", "ItemLift.binary", "ItemLift.default" ] }, { "page": "ItemOdds", "title": "Item Odds", "topics": [ "ItemOdds", "ItemOdds.binary", "ItemOdds.default" ] }, { "page": "ItemReport", "title": "Generate Item Report for Non-Binary Test Data", "topics": [ "ItemReport" ] }, { "page": "ItemStatistics", "title": "Simple Item Statistics", "topics": [ "ItemStatistics", "ItemStatistics.binary", "ItemStatistics.default", "ItemStatistics.ordinal" ] }, { "page": "ItemThreshold", "title": "Item Threshold", "topics": [ "ItemThreshold", "ItemThreshold.binary", "ItemThreshold.ordinal" ] }, { "page": "ItemTotalCorr", "title": "Item-Total Correlation", "topics": [ "ItemTotalCorr", "ItemTotalCorr.binary", "ItemTotalCorr.default", "ItemTotalCorr.ordinal" ] }, { "page": "J12S5000", "title": "J12S5000", "topics": [ "J12S5000" ] }, { "page": "J15S3810", "title": "J15S3810", "topics": [ "J15S3810" ] }, { "page": "J15S500", "title": "J15S500", "topics": [ "J15S500" ] }, { "page": "J20S400", "title": "J20S400", "topics": [ "J20S400" ] }, { "page": "J20S600", "title": "J20S600", "topics": [ "J20S600" ] }, { "page": "J21S300", "title": "J21S300", "topics": [ "J21S300" ] }, { "page": "J35S500", "title": "J35S500", "topics": [ "J35S500" ] }, { "page": "J35S5000", "title": "J35S5000", "topics": [ "J35S5000" ] }, { "page": "J35S515", "title": "J35S515", "topics": [ "J35S515" ] }, { "page": "J50S100", "title": "J50S100", "topics": [ "J50S100" ] }, { "page": "J5S10", "title": "J5S10", "topics": [ "J5S10" ] }, { "page": "J5S1000", "title": "J5S1000", "topics": [ "J5S1000" ] }, { "page": "JCRR", "title": "Joint Correct Response Rate", "topics": [ "JCRR", "JCRR.binary", "JCRR.default", "JCRR.nominal" ] }, { "page": "JointSampleSize", "title": "Joint Sample Size", "topics": [ "JointSampleSize", "JointSampleSize.binary", "JointSampleSize.default" ] }, { "page": "JSR", "title": "Joint Selection Rate", "topics": [ "JSR" ] }, { "page": "LCA", "title": "Latent Class Analysis", "topics": [ "LCA" ] }, { "page": "LD_param_est", "title": "LDparam set", "topics": [ "LD_param_est" ] }, { "page": "LDB", "title": "Local Dependence Biclustering", "topics": [ "LDB" ] }, { "page": "LDLRA", "title": "Local Dependence Latent Rank Analysis", "topics": [ "LDLRA" ] }, { "page": "LDLRA_PBIL", "title": "Structure Learning for LDLRA by PBIL algorithm", "topics": [ "LDLRA_PBIL" ] }, { "page": "LogisticModel", "title": "Four-Parameter Logistic Model", "topics": [ "LogisticModel" ] }, { "page": "longdataFormat", "title": "Long Format Data Conversion", "topics": [ "longdataFormat" ] }, { "page": "LRA", "title": "Latent Rank Analysis", "topics": [ "LRA", "LRA.binary", "LRA.default", "LRA.ordinal", "LRA.rated" ] }, { "page": "maxParents_penalty", "title": "Utility function for searching DAG", "topics": [ "maxParents_penalty" ] }, { "page": "MutualInformation", "title": "Mutual Information", "topics": [ "MutualInformation", "MutualInformation.binary", "MutualInformation.default", "MutualInformation.ordinal" ] }, { "page": "nrs", "title": "Number Right Score", "topics": [ "nrs", "nrs.binary", "nrs.default" ] }, { "page": "objective_function_IRT", "title": "Log-likelihood function used in the Maximization Step (M-Step).", "topics": [ "objective_function_IRT" ] }, { "page": "OmegaCoefficient", "title": "Omega Coefficient", "topics": [ "OmegaCoefficient" ] }, { "page": "passage", "title": "Passage Rate of Student", "topics": [ "passage", "passage.binary", "passage.default" ] }, { "page": "percentile", "title": "Student Percentile Ranks", "topics": [ "percentile", "percentile.binary", 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