{
  "_id": "6a229f49cd65a98ecbd58309",
  "Package": "simsem",
  "Type": "Package",
  "Title": "SIMulated Structural Equation Modeling",
  "Version": "0.5-17",
  "Date": "2025-04-02",
  "Authors@R": "c(person(given = \"Sunthud\", family = \"Pornprasertmanit\", role = \"aut\", email = \"psunthud@gmail.com\"), \nperson(given = \"Patrick\", family = \"Miller\", role = \"aut\", email=\"pmille13@nd.edu\"),\nperson(given = c(\"Alexander\", \"M.\"), family = \"Schoemann\", role = \"aut\", email=\"schoemanna@ecu.edu\", comment = c(ORCID = \"0000-0002-8479-8798\")),\nperson(given = c(\"Terrence\",\"D.\"), family = \"Jorgensen\", role = c(\"aut\", \"cre\"), email=\"TJorgensen314@gmail.com\", comment = c(ORCID = \"0000-0001-5111-6773\")),\nperson(given = \"Corbin\", family = \"Quick\", role = \"ctb\", email=\"qcorbin@hsph.harvard.edu\"))",
  "Maintainer": "Terrence D. Jorgensen <TJorgensen314@gmail.com>",
  "Description": "Provides an easy framework for Monte Carlo simulation in\nstructural equation modeling, which can be used for various\npurposes, such as such as model fit evaluation, power analysis,\nor missing data handling and planning.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
  "URL": "https://simsem.org/",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-05 09:59:57 UTC",
    "User": "root"
  },
  "Author": "Sunthud Pornprasertmanit [aut], Patrick Miller [aut], Alexander\nM. Schoemann [aut] (<https://orcid.org/0000-0002-8479-8798>),\nTerrence D. Jorgensen [aut, cre]\n(<https://orcid.org/0000-0001-5111-6773>), Corbin Quick [ctb]",
  "Repository": "https://tdjorgensen.r-universe.dev",
  "Date/Publication": "2025-04-02 12:30:01 UTC",
  "RemoteUrl": "https://github.com/cran/simsem",
  "RemoteRef": "HEAD",
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  "_user": "tdjorgensen",
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  "_created": "2026-06-05T09:59:57.000Z",
  "_published": "2026-06-05T10:04:57.273Z",
  "_distro": "noble",
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  "_buildurl": "https://github.com/r-universe/tdjorgensen/actions/runs/27008283734",
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  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/simsem",
  "_commit": {
    "id": "31622759338e23de3977568139e62dda9101a0a7",
    "author": "Terrence D. Jorgensen <TJorgensen314@gmail.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.5-17\n",
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  "_maintainer": {
    "name": "Terrence D. Jorgensen",
    "email": "tjorgensen314@gmail.com",
    "login": "tdjorgensen",
    "orcid": "0000-0001-5111-6773",
    "description": "Assistant Professor at University of Amsterdam",
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  "_dependencies": [
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  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 0,
  "_contributors": [
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      "count": 4,
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    },
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    "name": "Terrence",
    "description": "Assistant Professor at University of Amsterdam"
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  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/simsem"
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  "_mentions": 9,
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  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/simsem.html",
    "manual.pdf"
  ],
  "_realowner": "tdjorgensen",
  "_cranurl": false,
  "_releases": [
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      "version": "0.2-0",
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      "date": "2012-07-09"
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      "date": "2014-10-03"
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      "date": "2015-06-28"
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      "date": "2016-02-29"
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      "date": "2016-06-07"
    },
    {
      "version": "0.5-14",
      "date": "2018-06-03"
    },
    {
      "version": "0.5-15",
      "date": "2020-02-12"
    },
    {
      "version": "0.5-16",
      "date": "2021-03-28"
    },
    {
      "version": "0.5-17",
      "date": "2025-04-02"
    }
  ],
  "_exports": [
    "analyze",
    "anova",
    "bind",
    "bindDist",
    "binds",
    "coef",
    "combineSim",
    "continuousCoverage",
    "continuousPower",
    "createData",
    "draw",
    "estmodel",
    "estmodel.cfa",
    "estmodel.path",
    "estmodel.sem",
    "exportData",
    "findCoverage",
    "findFactorIntercept",
    "findFactorMean",
    "findFactorResidualVar",
    "findFactorTotalCov",
    "findFactorTotalVar",
    "findIndIntercept",
    "findIndMean",
    "findIndResidualVar",
    "findIndTotalVar",
    "findPossibleFactorCor",
    "findPower",
    "findRecursiveSet",
    "generate",
    "getCIwidth",
    "getCoverage",
    "getCutoff",
    "getCutoffNested",
    "getCutoffNonNested",
    "getExtraOutput",
    "getPopulation",
    "getPower",
    "getPowerFit",
    "getPowerFitNested",
    "getPowerFitNonNested",
    "impose",
    "imposeMissing",
    "inspect",
    "likRatioFit",
    "miss",
    "model",
    "model.cfa",
    "model.lavaan",
    "model.path",
    "model.sem",
    "multipleAllEqual",
    "plotCIwidth",
    "plotCoverage",
    "plotCutoff",
    "plotCutoffNested",
    "plotCutoffNonNested",
    "plotDist",
    "plotLogitMiss",
    "plotMisfit",
    "plotPower",
    "plotPowerFit",
    "plotPowerFitNested",
    "plotPowerFitNonNested",
    "popDiscrepancy",
    "popMisfitMACS",
    "pValue",
    "pValueNested",
    "pValueNonNested",
    "rawDraw",
    "setPopulation",
    "sim",
    "summary",
    "summaryConverge",
    "summaryFit",
    "summaryMisspec",
    "summaryParam",
    "summaryPopulation",
    "summarySeed",
    "summaryShort",
    "summaryTime"
  ],
  "_help": [
    {
      "page": "analyze",
      "title": "Data analysis using the model specification",
      "topics": [
        "analyze"
      ]
    },
    {
      "page": "anova",
      "title": "Provide a comparison of nested models and nonnested models across replications",
      "topics": [
        "anova,SimResult-method"
      ]
    },
    {
      "page": "bind",
      "title": "Specify matrices for Monte Carlo simulation of structural equation models",
      "topics": [
        "bind",
        "binds"
      ]
    },
    {
      "page": "bindDist",
      "title": "Create a data distribution object.",
      "topics": [
        "bindDist"
      ]
    },
    {
      "page": "coef",
      "title": "Extract parameter estimates from a simulation result",
      "topics": [
        "coef,SimResult-method"
      ]
    },
    {
      "page": "combineSim",
      "title": "Combine result objects",
      "topics": [
        "combineSim"
      ]
    },
    {
      "page": "continuousCoverage",
      "title": "Find coverage rate of model parameters when simulations have randomly varying parameters",
      "topics": [
        "continuousCoverage"
      ]
    },
    {
      "page": "continuousPower",
      "title": "Find power of model parameters when simulations have randomly varying parameters",
      "topics": [
        "continuousPower"
      ]
    },
    {
      "page": "createData",
      "title": "Create data from a set of drawn parameters.",
      "topics": [
        "createData"
      ]
    },
    {
      "page": "draw",
      "title": "Draw parameters from a 'SimSem' object.",
      "topics": [
        "draw"
      ]
    },
    {
      "page": "estmodel",
      "title": "Shortcut for data analysis template for simulation.",
      "topics": [
        "estmodel",
        "estmodel.cfa",
        "estmodel.path",
        "estmodel.sem"
      ]
    },
    {
      "page": "exportData",
      "title": "Export data sets for analysis with outside SEM program.",
      "topics": [
        "exportData"
      ]
    },
    {
      "page": "findCoverage",
      "title": "Find a value of independent variables that provides a given value of coverage rate",
      "topics": [
        "findCoverage"
      ]
    },
    {
      "page": "findFactorIntercept",
      "title": "Find factor intercept from regression coefficient matrix and factor total means",
      "topics": [
        "findFactorIntercept"
      ]
    },
    {
      "page": "findFactorMean",
      "title": "Find factor total means from regression coefficient matrix and factor intercept",
      "topics": [
        "findFactorMean"
      ]
    },
    {
      "page": "findFactorResidualVar",
      "title": "Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances",
      "topics": [
        "findFactorResidualVar"
      ]
    },
    {
      "page": "findFactorTotalCov",
      "title": "Find factor total covariance from regression coefficient matrix, factor residual covariance",
      "topics": [
        "findFactorTotalCov"
      ]
    },
    {
      "page": "findFactorTotalVar",
      "title": "Find factor total variances from regression coefficient matrix, factor (residual) correlations, and factor residual variances",
      "topics": [
        "findFactorTotalVar"
      ]
    },
    {
      "page": "findIndIntercept",
      "title": "Find indicator intercepts from factor loading matrix, total factor mean, and indicator mean.",
      "topics": [
        "findIndIntercept"
      ]
    },
    {
      "page": "findIndMean",
      "title": "Find indicator total means from factor loading matrix, total factor mean, and indicator intercept.",
      "topics": [
        "findIndMean"
      ]
    },
    {
      "page": "findIndResidualVar",
      "title": "Find indicator residual variances from factor loading matrix, total factor covariance, and total indicator variances.",
      "topics": [
        "findIndResidualVar"
      ]
    },
    {
      "page": "findIndTotalVar",
      "title": "Find indicator total variances from factor loading matrix, total factor covariance, and indicator residual variances.",
      "topics": [
        "findIndTotalVar"
      ]
    },
    {
      "page": "findPossibleFactorCor",
      "title": "Find the appropriate position for freely estimated correlation (or covariance) given a regression coefficient matrix",
      "topics": [
        "findPossibleFactorCor"
      ]
    },
    {
      "page": "findPower",
      "title": "Find a value of independent variables that provides a given value of power.",
      "topics": [
        "findPower"
      ]
    },
    {
      "page": "findRecursiveSet",
      "title": "Group variables regarding the position in mediation chain",
      "topics": [
        "findRecursiveSet"
      ]
    },
    {
      "page": "generate",
      "title": "Generate data using SimSem template",
      "topics": [
        "generate"
      ]
    },
    {
      "page": "getCIwidth",
      "title": "Find confidence interval width",
      "topics": [
        "getCIwidth"
      ]
    },
    {
      "page": "getCoverage",
      "title": "Find coverage rate of model parameters",
      "topics": [
        "getCoverage"
      ]
    },
    {
      "page": "getCutoff",
      "title": "Find fit indices cutoff given a priori alpha level",
      "topics": [
        "getCutoff"
      ]
    },
    {
      "page": "getCutoffNested",
      "title": "Find fit indices cutoff for nested model comparison given a priori alpha level",
      "topics": [
        "getCutoffNested"
      ]
    },
    {
      "page": "getCutoffNonNested",
      "title": "Find fit indices cutoff for non-nested model comparison given a priori alpha level",
      "topics": [
        "getCutoffNonNested"
      ]
    },
    {
      "page": "getExtraOutput",
      "title": "Get extra outputs from the result of simulation",
      "topics": [
        "getExtraOutput"
      ]
    },
    {
      "page": "getPopulation",
      "title": "Extract the data generation population model underlying a result object",
      "topics": [
        "getPopulation"
      ]
    },
    {
      "page": "getPower",
      "title": "Find power of model parameters",
      "topics": [
        "getPower"
      ]
    },
    {
      "page": "getPowerFit",
      "title": "Find power in rejecting alternative models based on fit indices criteria",
      "topics": [
        "getPowerFit"
      ]
    },
    {
      "page": "getPowerFitNested",
      "title": "Find power in rejecting nested models based on the differences in fit indices",
      "topics": [
        "getPowerFitNested"
      ]
    },
    {
      "page": "getPowerFitNonNested",
      "title": "Find power in rejecting non-nested models based on the differences in fit indices",
      "topics": [
        "getPowerFitNonNested",
        "getPowerFitNonNested,SimResult,SimResult,missing-method",
        "getPowerFitNonNested,SimResult,SimResult,vector-method",
        "getPowerFitNonNested-methods"
      ]
    },
    {
      "page": "imposeMissing",
      "title": "Impose MAR, MCAR, planned missingness, or attrition on a data set",
      "topics": [
        "impose",
        "imposeMissing"
      ]
    },
    {
      "page": "inspect",
      "title": "Extract information from a simulation result",
      "topics": [
        "inspect",
        "inspect,SimResult-method"
      ]
    },
    {
      "page": "likRatioFit",
      "title": "Find the likelihood ratio (or Bayes factor) based on the bivariate distribution of fit indices",
      "topics": [
        "likRatioFit"
      ]
    },
    {
      "page": "miss",
      "title": "Specifying the missing template to impose on a dataset",
      "topics": [
        "miss"
      ]
    },
    {
      "page": "model",
      "title": "Data generation template and analysis template for simulation.",
      "topics": [
        "model",
        "model.cfa",
        "model.path",
        "model.sem"
      ]
    },
    {
      "page": "modelLavaan",
      "title": "Build the data generation template and analysis template from the lavaan result",
      "topics": [
        "model.lavaan"
      ]
    },
    {
      "page": "multipleAllEqual",
      "title": "Test whether all objects are equal",
      "topics": [
        "multipleAllEqual"
      ]
    },
    {
      "page": "plotCIwidth",
      "title": "Plot a confidence interval width of a target parameter",
      "topics": [
        "plotCIwidth"
      ]
    },
    {
      "page": "plotCoverage",
      "title": "Make a plot of confidence interval coverage rates",
      "topics": [
        "plotCoverage"
      ]
    },
    {
      "page": "plotCutoff",
      "title": "Plot sampling distributions of fit indices with fit indices cutoffs",
      "topics": [
        "plotCutoff"
      ]
    },
    {
      "page": "plotCutoffNested",
      "title": "Plot sampling distributions of the differences in fit indices between nested models with fit indices cutoffs",
      "topics": [
        "plotCutoffNested"
      ]
    },
    {
      "page": "plotCutoffNonNested",
      "title": "Plot sampling distributions of the differences in fit indices between non-nested models with fit indices cutoffs",
      "topics": [
        "plotCutoffNonNested"
      ]
    },
    {
      "page": "plotDist",
      "title": "Plot a distribution of a data distribution object",
      "topics": [
        "plotDist"
      ]
    },
    {
      "page": "plotLogitMiss",
      "title": "Visualize the missing proportion when the logistic regression method is used.",
      "topics": [
        "plotLogitMiss"
      ]
    },
    {
      "page": "plotMisfit",
      "title": "Plot the population misfit in the result object",
      "topics": [
        "plotMisfit"
      ]
    },
    {
      "page": "plotPower",
      "title": "Make a power plot of a parameter given varying parameters",
      "topics": [
        "plotPower"
      ]
    },
    {
      "page": "plotPowerFit",
      "title": "Plot sampling distributions of fit indices that visualize power of rejecting datasets underlying misspecified models",
      "topics": [
        "plotPowerFit"
      ]
    },
    {
      "page": "plotPowerFitNested",
      "title": "Plot power of rejecting a nested model in a nested model comparison by each fit index",
      "topics": [
        "plotPowerFitNested"
      ]
    },
    {
      "page": "plotPowerFitNonNested",
      "title": "Plot power of rejecting a non-nested model based on a difference in fit index",
      "topics": [
        "plotPowerFitNonNested"
      ]
    },
    {
      "page": "popDiscrepancy",
      "title": "Find the discrepancy value between two means and covariance matrices",
      "topics": [
        "popDiscrepancy"
      ]
    },
    {
      "page": "popMisfitMACS",
      "title": "Find population misfit by sufficient statistics",
      "topics": [
        "popMisfitMACS"
      ]
    },
    {
      "page": "pValue",
      "title": "Find p-values (1 - percentile) by comparing a single analysis output from the result object",
      "topics": [
        "pValue"
      ]
    },
    {
      "page": "pValueNested",
      "title": "Find p-values (1 - percentile) for a nested model comparison",
      "topics": [
        "pValueNested"
      ]
    },
    {
      "page": "pValueNonNested",
      "title": "Find p-values (1 - percentile) for a non-nested model comparison",
      "topics": [
        "pValueNonNested"
      ]
    },
    {
      "page": "rawDraw",
      "title": "Draw values from vector or matrix objects",
      "topics": [
        "rawDraw"
      ]
    },
    {
      "page": "setPopulation",
      "title": "Set the data generation population model underlying an object",
      "topics": [
        "setPopulation"
      ]
    },
    {
      "page": "sim",
      "title": "Run a Monte Carlo simulation with a structural equation model.",
      "topics": [
        "sim"
      ]
    },
    {
      "page": "SimDataDist-class",
      "title": "Class '\"SimDataDist\"': Data distribution object",
      "topics": [
        "plotDist,SimDataDist-method",
        "SimDataDist-class",
        "summary,SimDataDist-method"
      ]
    },
    {
      "page": "SimMatrix-class",
      "title": "Matrix object: Random parameters matrix",
      "topics": [
        "SimMatrix-class",
        "summary,SimMatrix-method",
        "summaryShort,SimMatrix-method"
      ]
    },
    {
      "page": "SimMissing-class",
      "title": "Class '\"SimMissing\"'",
      "topics": [
        "SimMissing-class",
        "summary,SimMissing-method"
      ]
    },
    {
      "page": "SimResult-class",
      "title": "Class '\"SimResult\"': Simulation Result Object",
      "topics": [
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