{
  "_id": "6a1efea6b401979e7341a7a6",
  "Package": "lsasim",
  "Title": "Functions to Facilitate the Simulation of Large Scale Assessment\nData",
  "Version": "2.1.6",
  "Authors@R": "c(\nperson(\"Tyler\", \"Matta\",\nemail = \"tyler.matta@gmail.com\", role = \"aut\"),\nperson(\"Leslie\", \"Rutkowski\",\nemail = \"leslie.rutkowski@cemo.uio.no\", role = \"aut\"),\nperson(\"David\", \"Rutkowski\",\nemail = \"david.rutkowski@cemo.uio.no\", role = \"aut\"),\nperson(\"Yuan-Ling Linda\", \"Liaw\",\nemail = \"y.l.liaw@cemo.uio.no\", role = \"aut\"),\nperson(\"Kondwani Kajera\", \"Mughogho\",\nemail = \"k.k.mughogho@cemo.uio.no\", role = \"ctb\"),\nperson(\"Waldir\", \"Leoncio\",\nemail = \"w.l.netto@medisin.uio.no\", role = c(\"aut\", \"cre\")),\nperson(\"Sinan\", \"Yavuz\", role = \"ctb\"),\nperson(\"Paul\", \"Bailey\", role = \"ctb\")\n)",
  "BugReports": "https://github.com/tmatta/lsasim/issues",
  "Description": "Provides functions to simulate data from large-scale\neducational assessments, including background questionnaire\ndata and cognitive item responses that adhere to a\nmultiple-matrix sampled design. The theoretical foundation can\nbe found on Matta, T.H., Rutkowski, L., Rutkowski, D. et al.\n(2018) <doi:10.1186/s40536-018-0068-8>.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.3.2",
  "VignetteBuilder": "knitr",
  "Roxygen": "list(markdown = TRUE)",
  "Date": "2025-01-22",
  "Language": "en-US",
  "Repository": "https://tmatta.r-universe.dev",
  "Date/Publication": "2025-01-22 09:49:26 UTC",
  "RemoteUrl": "https://github.com/tmatta/lsasim",
  "RemoteRef": "HEAD",
  "RemoteSha": "da13d170f3e1544ba9cf50503a7ecfd36c2687b5",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-18 09:34:34 UTC",
    "User": "root"
  },
  "Author": "Tyler Matta [aut],\nLeslie Rutkowski [aut],\nDavid Rutkowski [aut],\nYuan-Ling Linda Liaw [aut],\nKondwani Kajera Mughogho [ctb],\nWaldir Leoncio [aut, cre],\nSinan Yavuz [ctb],\nPaul Bailey [ctb]",
  "Maintainer": "Waldir Leoncio <w.l.netto@medisin.uio.no>",
  "MD5sum": "2e57f42a50a63c6a97babf2f4a6e2140",
  "_user": "tmatta",
  "_type": "src",
  "_file": "lsasim_2.1.6.tar.gz",
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  "_filesize": 448557,
  "_sha256": "d14893a67f619b742168f5f6ba2ad09448278838db149f8f8bf5bfb69a27fe39",
  "_created": "2026-05-18T09:34:34.000Z",
  "_published": "2026-06-02T16:02:46.860Z",
  "_distro": "noble",
  "_jobs": [
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  "_buildurl": "https://github.com/r-universe/tmatta/actions/runs/26025228115",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/tmatta/lsasim",
  "_commit": {
    "id": "da13d170f3e1544ba9cf50503a7ecfd36c2687b5",
    "author": "Waldir Leoncio <w.l.netto@medisin.uio.no>",
    "committer": "Waldir Leoncio <w.l.netto@medisin.uio.no>",
    "message": "Merge branch 'release-2.1.6'\n",
    "time": 1737539366
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  "_maintainer": {
    "name": "Waldir Leoncio",
    "email": "w.l.netto@medisin.uio.no",
    "login": "wleoncio",
    "description": "Research Software Engineer @ocbe-uio",
    "uuid": 8234768
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.6.0",
      "role": "Depends"
    },
    {
      "package": "mvtnorm",
      "role": "Imports"
    },
    {
      "package": "cli",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "polycor",
      "role": "Imports"
    },
    {
      "package": "testthat",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "formatR",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "NAEPirtparams",
      "role": "Suggests"
    }
  ],
  "_owner": "tmatta",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 6,
  "_contributors": [
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      "user": "wleoncio",
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    {
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  ],
  "_userbio": {
    "uuid": 8396637,
    "type": "user",
    "name": "Tyler Matta"
  },
  "_downloads": {
    "count": 235,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/lsasim"
  },
  "_devurl": "https://github.com/tmatta/lsasim",
  "_searchresults": 18,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/lsasim.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/tmatta/lsasim",
  "_realowner": "tmatta",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.0.0",
      "date": "2017-02-23"
    },
    {
      "version": "1.0.1",
      "date": "2017-05-10"
    },
    {
      "version": "2.0.0",
      "date": "2019-09-13"
    },
    {
      "version": "2.0.1",
      "date": "2019-12-05"
    },
    {
      "version": "2.0.2",
      "date": "2020-09-10"
    },
    {
      "version": "2.1.0",
      "date": "2021-06-23"
    },
    {
      "version": "2.1.1",
      "date": "2021-06-24"
    },
    {
      "version": "2.1.2",
      "date": "2021-11-10"
    },
    {
      "version": "2.1.3",
      "date": "2023-03-28"
    },
    {
      "version": "2.1.4",
      "date": "2023-08-24"
    },
    {
      "version": "2.1.5",
      "date": "2024-05-06"
    },
    {
      "version": "2.1.6",
      "date": "2025-01-22"
    }
  ],
  "_exports": [
    "beta_gen",
    "block_design",
    "booklet_design",
    "booklet_sample",
    "brr",
    "calc_replicate_weights",
    "cluster_gen",
    "cluster_gen_separate",
    "cluster_gen_together",
    "convert_vector_to_list",
    "cor_gen",
    "cov_gen",
    "draw_cluster_structure",
    "gen_variable_n",
    "intraclass_cor",
    "irt_gen",
    "item_gen",
    "jackknife",
    "label_respondents",
    "proportion_gen",
    "pt_bis_conversion",
    "questionnaire_gen",
    "ranges",
    "recalc_final_weights",
    "replicate_var",
    "response_gen",
    "sample_from",
    "select",
    "trim_sample"
  ],
  "_datasets": [
    {
      "name": "pisa2012_math_block",
      "title": "PISA 2012 mathematics item - item block indicator matrix",
      "object": "pisa2012_math_block",
      "class": [
        "data.frame"
      ],
      "fields": [
        "item_name",
        "item_no",
        "block1",
        "block2",
        "block3",
        "block4",
        "block5",
        "block6",
        "block7",
        "block8",
        "block9",
        "block10"
      ],
      "rows": 109,
      "table": true,
      "tojson": true
    },
    {
      "name": "pisa2012_math_booklet",
      "title": "PISA 2012 mathematics item block - test booklet indicator matrix",
      "object": "pisa2012_math_booklet",
      "class": [
        "data.frame"
      ],
      "fields": [
        "booklet",
        "b1",
        "b2",
        "b3",
        "b4",
        "b5",
        "b6",
        "b7",
        "b8",
        "b9"
      ],
      "rows": 13,
      "table": true,
      "tojson": true
    },
    {
      "name": "pisa2012_math_item",
      "title": "Item parameter estimates for 2012 PISA mathematics assessment",
      "object": "pisa2012_math_item",
      "class": [
        "data.frame"
      ],
      "fields": [
        "item_name",
        "item",
        "b",
        "d1",
        "d2"
      ],
      "rows": 109,
      "table": true,
      "tojson": true
    },
    {
      "name": "pisa2012_q_cormat",
      "title": "Correlation matrix from the PISA 2012 background questionnaire",
      "object": "pisa2012_q_cormat",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "ST93Q01",
        "ST93Q03",
        "ST93Q04",
        "ST93Q06",
        "ST93Q07",
        "ST94Q05",
        "ST94Q06",
        "ST94Q09",
        "ST94Q10",
        "ST94Q14",
        "ST88Q01",
        "ST88Q02",
        "ST88Q03",
        "ST88Q04",
        "ST89Q02",
        "ST89Q03",
        "ST89Q04",
        "ST89Q05",
        "PV1MATH"
      ],
      "rows": 19,
      "table": true,
      "tojson": true
    },
    {
      "name": "pisa2012_q_marginal",
      "title": "Marginal proportions from the PISA 2012 background questionnaire",
      "object": "pisa2012_q_marginal",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "dot-onAttach",
      "title": "Prints welcome message on package load",
      "topics": [
        ".onAttach"
      ]
    },
    {
      "page": "anova.lsasimcluster",
      "title": "Generate an ANOVA table for LSASIM clusters",
      "topics": [
        "anova.lsasimcluster"
      ]
    },
    {
      "page": "attribute_cluster_labels",
      "title": "Attribute Labels in Hierarchical Structure",
      "topics": [
        "attribute_cluster_labels"
      ]
    },
    {
      "page": "beta_gen",
      "title": "Generate regression coefficients",
      "topics": [
        "beta_gen"
      ]
    },
    {
      "page": "block_design",
      "title": "Assignment of test items to blocks",
      "topics": [
        "block_design"
      ]
    },
    {
      "page": "booklet_design",
      "title": "Assignment of item blocks to test booklets",
      "topics": [
        "booklet_design"
      ]
    },
    {
      "page": "booklet_sample",
      "title": "Assignment of test booklets to test takers",
      "topics": [
        "booklet_sample"
      ]
    },
    {
      "page": "brr",
      "title": "Generate replicates of a dataset using Balanced Repeated Replication",
      "topics": [
        "brr"
      ]
    },
    {
      "page": "calc_n_tilde",
      "title": "Calculate ñ",
      "topics": [
        "calc_n_tilde"
      ]
    },
    {
      "page": "calc_replicate_weights",
      "title": "Calculate replicate weights and summary statistics",
      "topics": [
        "calc_replicate_weights"
      ]
    },
    {
      "page": "calc_se_rho",
      "title": "Calculate Standard Error of Intraclass Correlation",
      "topics": [
        "calc_se_rho"
      ]
    },
    {
      "page": "calc_var_between",
      "title": "Calculate variance between classes",
      "topics": [
        "calc_var_between"
      ]
    },
    {
      "page": "calc_var_tot",
      "title": "Calculate the total variance",
      "topics": [
        "calc_var_tot"
      ]
    },
    {
      "page": "calc_var_within",
      "title": "Calculate variance within classes",
      "topics": [
        "calc_var_within"
      ]
    },
    {
      "page": "check_condition",
      "title": "Check if an error condition is satisfied",
      "topics": [
        "check_condition"
      ]
    },
    {
      "page": "check_ignored_parameters",
      "title": "Checks if provided parameters are ignored",
      "topics": [
        "check_ignored_parameters"
      ]
    },
    {
      "page": "check_n_N_class",
      "title": "Check class of n or N",
      "topics": [
        "check_n_N_class"
      ]
    },
    {
      "page": "check_valid_structure",
      "title": "Check if List is Valid",
      "topics": [
        "check_valid_structure"
      ]
    },
    {
      "page": "cluster_gen",
      "title": "Generate cluster sample",
      "topics": [
        "cluster_gen"
      ]
    },
    {
      "page": "cluster_gen_separate",
      "title": "Generate cluster samples with individual questionnaires",
      "topics": [
        "cluster_gen_separate"
      ]
    },
    {
      "page": "cluster_gen_together",
      "title": "Generate cluster samples with lowest-level questionnaires",
      "topics": [
        "cluster_gen_together"
      ]
    },
    {
      "page": "cluster_message",
      "title": "Print messages about clusters",
      "topics": [
        "cluster_message"
      ]
    },
    {
      "page": "convert_vector_to_list",
      "title": "Convert Vector to Expanded List",
      "topics": [
        "convert_vector_to_list"
      ]
    },
    {
      "page": "cor_gen",
      "title": "Generation of random correlation matrix",
      "topics": [
        "cor_gen"
      ]
    },
    {
      "page": "cov_gen",
      "title": "Generation of covariance matrices",
      "topics": [
        "cov_gen"
      ]
    },
    {
      "page": "cov_yfz_gen",
      "title": "Generate latent regression covariance matrix",
      "topics": [
        "cov_yfz_gen"
      ]
    },
    {
      "page": "cov_yxw_gen",
      "title": "Setup full YXW covariance matrix",
      "topics": [
        "cov_yxw_gen"
      ]
    },
    {
      "page": "cov_yxz_gen",
      "title": "Generate analytical covariance matrix",
      "topics": [
        "cov_yxz_gen"
      ]
    },
    {
      "page": "customize_summary",
      "title": "Customize Summary",
      "topics": [
        "customize_summary"
      ]
    },
    {
      "page": "draw_cluster_structure",
      "title": "Draw Cluster Structure",
      "topics": [
        "draw_cluster_structure"
      ]
    },
    {
      "page": "gen_cat_prop",
      "title": "Generates cat_prop for questionnaire_gen",
      "topics": [
        "gen_cat_prop"
      ]
    },
    {
      "page": "gen_variable_n",
      "title": "Randomly generate the quantity of background variables",
      "topics": [
        "gen_variable_n"
      ]
    },
    {
      "page": "gen_X_W_cluster",
      "title": "Generate n_X and n_W for clusters",
      "topics": [
        "gen_X_W_cluster"
      ]
    },
    {
      "page": "intraclass_cor",
      "title": "Intraclass correlation",
      "topics": [
        "intraclass_cor"
      ]
    },
    {
      "page": "irt_gen",
      "title": "Simulate item responses from an item response model",
      "topics": [
        "irt_gen"
      ]
    },
    {
      "page": "item_gen",
      "title": "Generation of item parameters from uniform distributions",
      "topics": [
        "item_gen"
      ]
    },
    {
      "page": "jackknife",
      "title": "Generate replicates of a dataset using Jackknife",
      "topics": [
        "jackknife"
      ]
    },
    {
      "page": "label_respondents",
      "title": "Label respondents",
      "topics": [
        "label_respondents"
      ]
    },
    {
      "page": "lambda_gen",
      "title": "Randomly generate a matrix of factor loadings",
      "topics": [
        "lambda_gen"
      ]
    },
    {
      "page": "lsasim",
      "title": "lsasim: A package for simulating large scale assessment data",
      "topics": [
        "lsasim-package",
        "lsasim"
      ]
    },
    {
      "page": "pisa2012_math_block",
      "title": "PISA 2012 mathematics item - item block indicator matrix",
      "topics": [
        "pisa2012_math_block"
      ]
    },
    {
      "page": "pisa2012_math_booklet",
      "title": "PISA 2012 mathematics item block - test booklet indicator matrix",
      "topics": [
        "pisa2012_math_booklet"
      ]
    },
    {
      "page": "pisa2012_math_item",
      "title": "Item parameter estimates for 2012 PISA mathematics assessment",
      "topics": [
        "pisa2012_math_item"
      ]
    },
    {
      "page": "pisa2012_q_cormat",
      "title": "Correlation matrix from the PISA 2012 background questionnaire",
      "topics": [
        "pisa2012_q_cormat"
      ]
    },
    {
      "page": "pisa2012_q_marginal",
      "title": "Marginal proportions from the PISA 2012 background questionnaire",
      "topics": [
        "pisa2012_q_marginal"
      ]
    },
    {
      "page": "pluralize",
      "title": "Pluralize words",
      "topics": [
        "pluralize"
      ]
    },
    {
      "page": "print_anova",
      "title": "Print the ANOVA table",
      "topics": [
        "print_anova"
      ]
    },
    {
      "page": "proportion_gen",
      "title": "Generation of random cumulative proportions",
      "topics": [
        "proportion_gen"
      ]
    },
    {
      "page": "pt_bis_conversion",
      "title": "Analytical point-biserial conversion",
      "topics": [
        "pt_bis_conversion"
      ]
    },
    {
      "page": "questionnaire_gen",
      "title": "Generation of ordinal and continuous variables",
      "topics": [
        "questionnaire_gen"
      ]
    },
    {
      "page": "questionnaire_gen_family",
      "title": "Generation of ordinal and continuous variables",
      "topics": [
        "questionnaire_gen_family"
      ]
    },
    {
      "page": "questionnaire_gen_polychoric",
      "title": "Generation of ordinal and continuous variables",
      "topics": [
        "questionnaire_gen_polychoric"
      ]
    },
    {
      "page": "ranges",
      "title": "Defines vector as range",
      "topics": [
        "ranges"
      ]
    },
    {
      "page": "recalc_final_weights",
      "title": "Recalculate final weights",
      "topics": [
        "recalc_final_weights"
      ]
    },
    {
      "page": "replicate_var",
      "title": "Sampling variance of the mean for replications",
      "topics": [
        "replicate_var"
      ]
    },
    {
      "page": "response_gen",
      "title": "Generation of item response data using a rotated block design",
      "topics": [
        "response_gen"
      ]
    },
    {
      "page": "rzeropois",
      "title": "Generate data from a Zero-truncated Poisson",
      "topics": [
        "rzeropois"
      ]
    },
    {
      "page": "sample_from",
      "title": "Sample from population structure",
      "topics": [
        "sample_from"
      ]
    },
    {
      "page": "sample_within_range",
      "title": "Sample from range",
      "topics": [
        "sample_within_range"
      ]
    },
    {
      "page": "select",
      "title": "Transform regular vector into selection vector",
      "topics": [
        "select"
      ]
    },
    {
      "page": "split_cat_prop",
      "title": "Split variables in cat_prop",
      "topics": [
        "split_cat_prop"
      ]
    },
    {
      "page": "summary_2",
      "title": "Dataset summary statistics",
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