align.plots             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.
as.data.frame.covariate.balance
                        Returns the overall effects as a data frame.
covariate.balance       Estimate covariate effect sizes before and
                        after propensity score adjustment.
covariateBalance        Calculate covariate effect size differences
                        before and after stratification.
cv.trans.psa            Transformation of Factors to Individual Levels
difftable.plot          This function produces a ggplot2 figure
                        containing the mean differences for each level
                        two, or cluster.
getPropensityScores     Returns a data frame with two columns
                        corresponding to the level 2 variable and the
                        fitted value from the logistic regression.
getStrata               Returns a data frame with two columns
                        corresponding to the level 2 variable and the
                        leaves from the conditional inference trees.
is.mlpsa                Returns true if the object is of type 'mlpsa'
loess.plot              Loess plot with density distributions for
                        propensity scores and outcomes on top and
                        right, respectively.
lsos                    Nicer list of objects in memory. Particularly
                        useful for analysis of large data.  <URL: #
                        http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session>
missing.plot            Returns a heat map graphic representing
                        missingness of variables grouped by the given
                        grouping vector.
mlpsa                   This function will perform phase II of the
                        multilevel propensity score analysis.
mlpsa.circ.plot         Plots the results of a multilevel propensity
                        score model.
mlpsa.ctree             Estimates propensity scores using the recursive
                        partitioning in a conditional inference
                        framework.
mlpsa.difference.plot   Creates a graphic summarizing the differences
                        between treatment and comparison groups within
                        and across level two clusters.
mlpsa.distribution.plot
                        Plots distribution for either the treatment or
                        comparison group.
mlpsa.logistic          Estimates propensity scores using logistic
                        regression.
multilevelPSA-package   Multilevel Propensity Score Analysis
pisa.colnames           Mapping of variables in 'pisana' with full
                        descriptions.
pisa.countries          Data frame mapping PISA countries to their
                        three letter abbreviation.
pisa.psa.cols           Character vector representing the list of
                        covariates used for estimating propensity
                        scores.
pisana                  North American (i.e. Canada, Mexico, and United
                        States) student results of the 2009 Programme
                        of International Student Assessment.
plot.covariate.balance
                        Multiple covariate balance assessment plot.
plot.mlpsa              Plots the results of a multilevel propensity
                        score model.
plot.psrange            Plots densities and ranges for the propensity
                        scores.
print.covariate.balance
                        Prints the overall effects before and after
                        propensity score adjustment.
print.mlpsa             Prints basic information about a 'mlpsa' class.
print.psrange           Prints information about a psrange result.
print.xmlpsa            Prints the results of 'mlpsa' and
                        'xtable.mlpsa'.
psrange                 Estimates models with increasing number of
                        comparison subjects starting from 1:1 to using
                        all available comparison group subjects.
summary.mlpsa           Provides a summary of a 'mlpsa' class.
summary.psrange         Prints the summary results of psrange.
tree.plot               Heat map representing variables used in a
                        conditional inference tree across level 2
                        variables.
xtable.mlpsa            Prints the results of 'mlpsa' as a LaTeX table.
