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multilevelPSA (version 1.2.5)

Multilevel Propensity Score Analysis

Description

Conducts and visualizes propensity score analysis for multilevel, or clustered data. Bryer & Pruzek (2011) .

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install.packages('multilevelPSA')

Monthly Downloads

170

Version

1.2.5

License

GPL (>= 2)

Issues

0

Pull Requests

0

Stars

16

Forks

5

Maintainer

Jason Bryer

Last Published

March 22nd, 2018

Functions in multilevelPSA (1.2.5)

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.
is.mlpsa

Returns true if the object is of type mlpsa
lsos

Nicer list of objects in memory. Particularly useful for analysis of large data. # http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session
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.
cv.trans.psa

Transformation of Factors to Individual Levels
missing.plot

Returns a heat map graphic representing missingness of variables grouped by the given grouping vector.
difftable.plot

This function produces a ggplot2 figure containing the mean differences for each level two, or cluster.
as.data.frame.covariate.balance

Returns the overall effects as a data frame.
print.psrange

Prints information about a psrange result.
getStrata

Returns a data frame with two columns corresponding to the level 2 variable and the leaves from the conditional inference trees.
getPropensityScores

Returns a data frame with two columns corresponding to the level 2 variable and the fitted value from the logistic regression.
print.xmlpsa

Prints the results of mlpsa and xtable.mlpsa.
plot.mlpsa

Plots the results of a multilevel propensity score model.
print.mlpsa

Prints basic information about a mlpsa class.
plot.psrange

Plots densities and ranges for the propensity scores.
loess.plot

Loess plot with density distributions for propensity scores and outcomes on top and right, respectively.
summary.psrange

Prints the summary results of psrange.
pisa.colnames

Mapping of variables in pisana with full descriptions.
tree.plot

Heat map representing variables used in a conditional inference tree across level 2 variables.
pisa.countries

Data frame mapping PISA countries to their three letter abbreviation.
mlpsa.distribution.plot

Plots distribution for either the treatment or comparison group.
mlpsa

This function will perform phase II of the multilevel propensity score analysis.
pisa.psa.cols

Character vector representing the list of covariates used for estimating propensity scores.
mlpsa.circ.plot

Plots the results of a multilevel propensity score model.
mlpsa.logistic

Estimates propensity scores using logistic regression.
pisana

North American (i.e. Canada, Mexico, and United States) student results of the 2009 Programme of International Student Assessment.
covariate.balance

Estimate covariate effect sizes before and after propensity score adjustment.
print.covariate.balance

Prints the overall effects before and after propensity score adjustment.
plot.covariate.balance

Multiple covariate balance assessment plot.
covariateBalance

Calculate covariate effect size differences before and after stratification.
xtable.mlpsa

Prints the results of mlpsa as a LaTeX table.
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.
zeroGrob

The zero grob draws nothing and has zero size.
multilevelPSA-package

Multilevel Propensity Score Analysis