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  "Description": "Conducts and visualizes propensity score analysis for\nmultilevel, or clustered data. Bryer & Pruzek (2011)\n<doi:10.1080/00273171.2011.636693>.",
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    "mlpsa.distribution.plot",
    "mlpsa.logistic",
    "psrange",
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        "Variable",
        "ShortDesc",
        "Desc"
      ],
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      "table": true,
      "tojson": true
    },
    {
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        "Country"
      ],
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      "table": true,
      "tojson": true
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      "tojson": true
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      "name": "pisana",
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        "SCHOOLID",
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        "ST21Q03",
        "ST21Q04",
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        "ST31Q03",
        "ST31Q05",
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        "ST31Q07",
        "ST32Q01",
        "ST32Q02",
        "ST32Q03",
        "PV1MATH",
        "PV2MATH",
        "PV3MATH",
        "PV4MATH",
        "PV5MATH",
        "PV1READ",
        "PV2READ",
        "PV3READ",
        "PV4READ",
        "PV5READ",
        "PV1SCIE",
        "PV2SCIE",
        "PV3SCIE",
        "PV4SCIE",
        "PV5SCIE",
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        "STRATIO"
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    {
      "page": "multilevelPSA-package",
      "title": "Multilevel Propensity Score Analysis",
      "topics": [
        "multilevelPSA-package",
        "multilevelPSA"
      ]
    },
    {
      "page": "align.plots",
      "title": "Adapted from ggExtra package which is no longer available. This is related to an experimental mlpsa plot that will combine the circular plot along with the two individual distributions.",
      "topics": [
        "align.plots"
      ]
    },
    {
      "page": "as.data.frame.covariate.balance",
      "title": "Returns the overall effects as a data frame.",
      "topics": [
        "as.data.frame.covariate.balance"
      ]
    },
    {
      "page": "covariate.balance",
      "title": "Estimate covariate effect sizes before and after propensity score adjustment.",
      "topics": [
        "covariate.balance"
      ]
    },
    {
      "page": "covariateBalance",
      "title": "Calculate covariate effect size differences before and after stratification.",
      "topics": [
        "covariateBalance"
      ]
    },
    {
      "page": "cv.trans.psa",
      "title": "Transformation of Factors to Individual Levels",
      "topics": [
        "cv.trans.psa"
      ]
    },
    {
      "page": "difftable.plot",
      "title": "This function produces a ggplot2 figure containing the mean differences for each level two, or cluster.",
      "topics": [
        "difftable.plot"
      ]
    },
    {
      "page": "getPropensityScores",
      "title": "Returns a data frame with two columns corresponding to the level 2 variable and the fitted value from the logistic regression.",
      "topics": [
        "getPropensityScores"
      ]
    },
    {
      "page": "getStrata",
      "title": "Returns a data frame with two columns corresponding to the level 2 variable and the leaves from the conditional inference trees.",
      "topics": [
        "getStrata"
      ]
    },
    {
      "page": "is.mlpsa",
      "title": "Returns true if the object is of type 'mlpsa'",
      "topics": [
        "is.mlpsa"
      ]
    },
    {
      "page": "loess.plot",
      "title": "Loess plot with density distributions for propensity scores and outcomes on top and right, respectively.",
      "topics": [
        "loess.plot"
      ]
    },
    {
      "page": "lsos",
      "title": "Nicer list of objects in memory. Particularly useful for analysis of large data. https://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session",
      "topics": [
        "lsos"
      ]
    },
    {
      "page": "missing.plot",
      "title": "Returns a heat map graphic representing missingness of variables grouped by the given grouping vector.",
      "topics": [
        "missing.plot"
      ]
    },
    {
      "page": "mlpsa",
      "title": "This function will perform phase II of the multilevel propensity score analysis.",
      "topics": [
        "mlpsa"
      ]
    },
    {
      "page": "mlpsa.circ.plot",
      "title": "Plots the results of a multilevel propensity score model.",
      "topics": [
        "mlpsa.circ.plot"
      ]
    },
    {
      "page": "mlpsa.ctree",
      "title": "Estimates propensity scores using the recursive partitioning in a conditional inference framework.",
      "topics": [
        "mlpsa.ctree"
      ]
    },
    {
      "page": "mlpsa.difference.plot",
      "title": "Creates a graphic summarizing the differences between treatment and comparison groups within and across level two clusters.",
      "topics": [
        "mlpsa.difference.plot"
      ]
    },
    {
      "page": "mlpsa.distribution.plot",
      "title": "Plots distribution for either the treatment or comparison group.",
      "topics": [
        "mlpsa.distribution.plot"
      ]
    },
    {
      "page": "mlpsa.logistic",
      "title": "Estimates propensity scores using logistic regression.",
      "topics": [
        "mlpsa.logistic"
      ]
    },
    {
      "page": "pisa.colnames",
      "title": "Mapping of variables in `pisana` with full descriptions.",
      "topics": [
        "pisa.colnames"
      ]
    },
    {
      "page": "pisa.countries",
      "title": "Data frame mapping PISA countries to their three letter abbreviation.",
      "topics": [
        "pisa.countries"
      ]
    },
    {
      "page": "pisa.psa.cols",
      "title": "Character vector representing the list of covariates used for estimating propensity scores.",
      "topics": [
        "pisa.psa.cols"
      ]
    },
    {
      "page": "pisana",
      "title": "North American (i.e. Canada, Mexico, and United States) student results of the 2009 Programme of International Student Assessment.",
      "topics": [
        "pisana"
      ]
    },
    {
      "page": "plot.covariate.balance",
      "title": "Multiple covariate balance assessment plot.",
      "topics": [
        "plot.covariate.balance"
      ]
    },
    {
      "page": "plot.mlpsa",
      "title": "Plots the results of a multilevel propensity score model.",
      "topics": [
        "plot.mlpsa"
      ]
    },
    {
      "page": "plot.psrange",
      "title": "Plots densities and ranges for the propensity scores.",
      "topics": [
        "plot.psrange"
      ]
    },
    {
      "page": "print.covariate.balance",
      "title": "Prints the overall effects before and after propensity score adjustment.",
      "topics": [
        "print.covariate.balance"
      ]
    },
    {
      "page": "print.mlpsa",
      "title": "Prints basic information about a 'mlpsa' class.",
      "topics": [
        "print.mlpsa"
      ]
    },
    {
      "page": "print.psrange",
      "title": "Prints information about a psrange result.",
      "topics": [
        "print.psrange"
      ]
    },
    {
      "page": "print.xmlpsa",
      "title": "Prints the results of [mlpsa()] and [xtable.mlpsa()].",
      "topics": [
        "print.xmlpsa"
      ]
    },
    {
      "page": "psrange",
      "title": "Estimates models with increasing number of comparison subjects starting from 1:1 to using all available comparison group subjects.",
      "topics": [
        "psrange"
      ]
    },
    {
      "page": "summary.mlpsa",
      "title": "Provides a summary of a 'mlpsa' class.",
      "topics": [
        "summary.mlpsa"
      ]
    },
    {
      "page": "summary.psrange",
      "title": "Prints the summary results of psrange.",
      "topics": [
        "summary.psrange"
      ]
    },
    {
      "page": "tree.plot",
      "title": "Heat map representing variables used in a conditional inference tree across level 2 variables.",
      "topics": [
        "tree.plot"
      ]
    },
    {
      "page": "xtable.mlpsa",
      "title": "Prints the results of [mlpsa()] as a LaTeX table.",
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