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  "Title": "Estimation of the Structural Topic Model",
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  "Authors@R": "c(\nperson(\"Margaret\", \"Roberts\", email=\"meroberts@ucsd.edu\", role=\"aut\"),\nperson(\"Brandon\", \"Stewart\", email=\"bms4@princeton.edu\", role=c(\"aut\",\"cre\")),\nperson(\"Dustin\", \"Tingley\", email=\"dtingley@gov.harvard.edu\", role=\"aut\"),\nperson(\"Kenneth\",\"Benoit\", email=\"kbenoit@lse.ac.uk\", role=\"ctb\"))",
  "Description": "The Structural Topic Model (STM) allows researchers to\nestimate topic models with document-level covariates. The\npackage also includes tools for model selection, visualization,\nand estimation of topic-covariate regressions. Methods\ndeveloped in Roberts et. al. (2014) <doi:10.1111/ajps.12103>\nand Roberts et. al. (2016) <doi:10.1080/01621459.2016.1141684>.\nVignette is Roberts et. al. (2019) <doi:10.18637/jss.v091.i02>.",
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  "Date/Publication": "2026-01-14 15:52:16 UTC",
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  "Author": "Margaret Roberts [aut],\nBrandon Stewart [aut, cre],\nDustin Tingley [aut],\nKenneth Benoit [ctb]",
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    "calcscore",
    "checkBeta",
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    "cloud",
    "convertCorpus",
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    "eval.heldout",
    "exclusivity",
    "findThoughts",
    "findTopic",
    "fitNewDocuments",
    "js.estimate",
    "labelTopics",
    "make.dt",
    "make.heldout",
    "makeDesignMatrix",
    "manyTopics",
    "multiSTM",
    "optimizeDocument",
    "permutationTest",
    "plot.estimateEffect",
    "plot.searchK",
    "plot.STM",
    "plot.topicCorr",
    "plotModels",
    "plotQuote",
    "plotRemoved",
    "plotTopicLoess",
    "prepDocuments",
    "readCorpus",
    "readLdac",
    "s",
    "sageLabels",
    "searchK",
    "selectModel",
    "semanticCoherence",
    "stm",
    "textProcessor",
    "thetaPosterior",
    "toLDAvis",
    "toLDAvisJson",
    "topicCorr",
    "topicLasso",
    "topicQuality",
    "writeLdac"
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      "class": [
        "data.frame"
      ],
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        "treatment",
        "pid_rep",
        "open.ended.response"
      ],
      "rows": 341,
      "table": true,
      "tojson": true
    },
    {
      "name": "gadarianFit",
      "title": "Gadarian and Albertson data",
      "object": "gadarianFit",
      "class": [
        "STM"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
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      "title": "CMU 2008 Political Blog Corpus",
      "object": "poliblog5k",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": true
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      "title": "CMU 2008 Political Blog Corpus",
      "object": "poliblog5k",
      "class": [
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        "day",
        "blog",
        "text"
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      "rows": 5000,
      "table": true,
      "tojson": true
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      "title": "CMU 2008 Political Blog Corpus",
      "object": "poliblog5k",
      "class": [
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
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  "_help": [
    {
      "page": "stm-package",
      "title": "Structural Topic Model",
      "topics": [
        "stm-package"
      ]
    },
    {
      "page": "alignCorpus",
      "title": "Align the vocabulary of a new corpus to an old corpus",
      "topics": [
        "alignCorpus"
      ]
    },
    {
      "page": "asSTMCorpus",
      "title": "STM Corpus Coercion",
      "topics": [
        "asSTMCorpus"
      ]
    },
    {
      "page": "checkBeta",
      "title": "Looks for words that load exclusively onto a topic",
      "topics": [
        "checkBeta"
      ]
    },
    {
      "page": "checkResiduals",
      "title": "Residual dispersion test for topic number",
      "topics": [
        "checkResiduals"
      ]
    },
    {
      "page": "cloud",
      "title": "Plot a wordcloud",
      "topics": [
        "cloud"
      ]
    },
    {
      "page": "convertCorpus",
      "title": "Convert 'stm' formatted documents to another format",
      "topics": [
        "convertCorpus"
      ]
    },
    {
      "page": "estimateEffect",
      "title": "Estimates regressions using an STM object",
      "topics": [
        "estimateEffect"
      ]
    },
    {
      "page": "findThoughts",
      "title": "Find Thoughts",
      "topics": [
        "findThoughts",
        "plot.findThoughts",
        "print.findThoughts"
      ]
    },
    {
      "page": "findTopic",
      "title": "Find topics that contain user specified words.",
      "topics": [
        "findTopic"
      ]
    },
    {
      "page": "fitNewDocuments",
      "title": "Fit New Documents",
      "topics": [
        "fitNewDocuments"
      ]
    },
    {
      "page": "gadarian",
      "title": "Gadarian and Albertson data",
      "topics": [
        "gadarian",
        "gadarianFit"
      ]
    },
    {
      "page": "labelTopics",
      "title": "Label topics",
      "topics": [
        "labelTopics",
        "print.labelTopics"
      ]
    },
    {
      "page": "make.dt",
      "title": "Make a 'data.table' of topic proportions.",
      "topics": [
        "make.dt"
      ]
    },
    {
      "page": "make.heldout",
      "title": "Heldout Likelihood by Document Completion",
      "topics": [
        "eval.heldout",
        "make.heldout"
      ]
    },
    {
      "page": "manyTopics",
      "title": "Performs model selection across separate STM's that each assume different numbers of topics.",
      "topics": [
        "manyTopics"
      ]
    },
    {
      "page": "multiSTM",
      "title": "Analyze Stability of Local STM Mode",
      "topics": [
        "multiSTM",
        "print.MultimodDiagnostic"
      ]
    },
    {
      "page": "optimizeDocument",
      "title": "Optimize Document",
      "topics": [
        "optimizeDocument"
      ]
    },
    {
      "page": "permutationTest",
      "title": "Permutation test of a binary covariate.",
      "topics": [
        "permutationTest"
      ]
    },
    {
      "page": "plot.estimateEffect",
      "title": "Plot effect of covariates on topics",
      "topics": [
        "plot.estimateEffect"
      ]
    },
    {
      "page": "plot.MultimodDiagnostic",
      "title": "Plotting Method for Multimodality Diagnostic Objects",
      "topics": [
        "plot.MultimodDiagnostic"
      ]
    },
    {
      "page": "plot.searchK",
      "title": "Plots diagnostic values resulting from searchK",
      "topics": [
        "plot.searchK"
      ]
    },
    {
      "page": "plot.STM",
      "title": "Functions for plotting STM objects",
      "topics": [
        "plot.STM"
      ]
    },
    {
      "page": "plot.STMpermute",
      "title": "Plot an STM permutation test.",
      "topics": [
        "plot.STMpermute"
      ]
    },
    {
      "page": "plot.topicCorr",
      "title": "Plot a topic correlation graph",
      "topics": [
        "plot.topicCorr"
      ]
    },
    {
      "page": "plotModels",
      "title": "Plots semantic coherence and exclusivity for high likelihood models outputted from selectModel.",
      "topics": [
        "plotModels"
      ]
    },
    {
      "page": "plotQuote",
      "title": "Plots strings",
      "topics": [
        "plotQuote"
      ]
    },
    {
      "page": "plotRemoved",
      "title": "Plot documents, words and tokens removed at various word thresholds",
      "topics": [
        "plotRemoved"
      ]
    },
    {
      "page": "plotTopicLoess",
      "title": "Plot some effects with loess",
      "topics": [
        "plotTopicLoess"
      ]
    },
    {
      "page": "poliblog5k",
      "title": "CMU 2008 Political Blog Corpus",
      "topics": [
        "poliblog5k",
        "poliblog5k.docs",
        "poliblog5k.meta",
        "poliblog5k.voc"
      ]
    },
    {
      "page": "prepDocuments",
      "title": "Prepare documents for analysis with 'stm'",
      "topics": [
        "prepDocuments"
      ]
    },
    {
      "page": "readCorpus",
      "title": "Read in a corpus file.",
      "topics": [
        "readCorpus"
      ]
    },
    {
      "page": "readLdac",
      "title": "Read in a .ldac Formatted File",
      "topics": [
        "readLdac"
      ]
    },
    {
      "page": "s",
      "title": "Make a B-spline Basis Function",
      "topics": [
        "s"
      ]
    },
    {
      "page": "sageLabels",
      "title": "Displays verbose labels that describe topics and topic-covariate groups in depth.",
      "topics": [
        "print.sageLabels",
        "sageLabels"
      ]
    },
    {
      "page": "searchK",
      "title": "Computes diagnostic values for models with different values of K (number of topics).",
      "topics": [
        "searchK"
      ]
    },
    {
      "page": "selectModel",
      "title": "Assists the user in selecting the best STM model.",
      "topics": [
        "selectModel"
      ]
    },
    {
      "page": "stm",
      "title": "Variational EM for the Structural Topic Model",
      "topics": [
        "stm"
      ]
    },
    {
      "page": "summary.estimateEffect",
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