multilevelPSA: Multilevel Propensity Score Analysis

Functions to estimate and visualize propensity score analysis for multilevel, or clustered, data.

Install the latest version of this package by entering the following in R:
AuthorJason Bryer <>
Date of publication2015-12-28 21:43:03
MaintainerJason Bryer <>
LicenseGPL (>= 2)

View on CRAN

Man pages

align.plots: Adapted from ggExtra package which is no longer available.... Returns the overall effects as a data frame.

covariate.balance: Estimate covariate effect sizes before and after propensity...

covariateBalance: Calculate covariate effect size differences before and after...

cv.trans.psa: Transformation of Factors to Individual Levels

difftable.plot: This function produces a ggplot2 figure contianing the mean...

getPropensityScores: Returns a data frame with two columns corresponding to the...

getStrata: Returns a data frame with two columns corresponding to the...

is.mlpsa: Returns true if the object is of type 'mlpsa'

loess.plot: Loess plot with density distributions for propensity scores...

lsos: Nicer list of objects in memory. Particularly useful for...

missing.plot: Returns a heat map graphic representing missinging of...

mlpsa: This function will perform phase II of the multilevel...

mlpsa.circ.plot: Plots the results of a multilevel propensity score model.

mlpsa.ctree: Estimates propensity scores using the recursive partitioning...

mlpsa.difference.plot: Creates a graphic summarizing the differences between...

mlpsa.distribution.plot: Plots distribution for either the treatment or comparison...

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...

pisana: North American (i.e. Canada, Mexico, and United States)...

pisa.psa.cols: Character vector representing the list of covariates used for...

plot.covariate.balance: Multiple covariate blance 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...

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 comparision...

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...

xtable.mlpsa: Prints the results of 'mlpsa' as a LaTeX table.

zeroGrob: The zero grob draws nothing and has zero size.


align.plots Man page Man page
covariate.balance Man page
covariateBalance Man page
cv.trans.psa Man page
difftable.plot Man page
getPropensityScores Man page
getStrata Man page
is.mlpsa Man page
loess.plot Man page
lsos Man page
missing.plot Man page
mlpsa Man page
mlpsa.circ.plot Man page
mlpsa.ctree Man page
mlpsa.difference.plot Man page
mlpsa.distribution.plot Man page
mlpsa.logistic Man page
multilevelPSA Man page
multilevelPSA-package Man page
pisa.colnames Man page
pisa.countries Man page
pisana Man page
pisa.psa.cols Man page
plot.covariate.balance Man page
plot.mlpsa Man page
plot.psrange Man page
print.covariate.balance Man page
print.mlpsa Man page
print.psrange Man page
print.xmlpsa Man page
psrange Man page
summary.mlpsa Man page
summary.psrange Man page
tree.plot Man page
xtable.mlpsa Man page
zeroGrob Man page


Questions? Problems? Suggestions? or email at

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.