Multilevel Propensity Score Analysis

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Documentation for package ‘multilevelPSA’ version 1.2.5

• DESCRIPTION file.
• Code demos. Use demo() to run them.
• Package NEWS.

Help Pages

multilevelPSA-package	Multilevel Propensity Score Analysis
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	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.