Package: multilevelPSA 1.2.5

multilevelPSA: Multilevel Propensity Score Analysis

Conducts and visualizes propensity score analysis for multilevel, or clustered data. Bryer & Pruzek (2011) <doi:10.1080/00273171.2011.636693>.

Authors:Jason Bryer <[email protected]>

multilevelPSA_1.2.5.tar.gz
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multilevelPSA.pdf |multilevelPSA.html✨
multilevelPSA/json (API)
NEWS

# Install 'multilevelPSA' in R:
install.packages('multilevelPSA', repos = c('https://jbryer.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jbryer/multilevelpsa/issues

Datasets:
  • 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.

On CRAN:

16 exports 16 stars 1.87 score 50 dependencies 78 scripts 359 downloads

Last updated 4 years agofrom:933f88dd2b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 21 2024
R-4.5-winOKAug 21 2024
R-4.5-linuxOKAug 21 2024
R-4.4-winOKAug 21 2024
R-4.4-macOKAug 21 2024
R-4.3-winOKAug 21 2024
R-4.3-macOKAug 21 2024

Exports:covariate.balancedifftable.plotgetPropensityScoresgetStratais.mlpsaloess.plotlsosmissing.plotmlpsamlpsa.circ.plotmlpsa.ctreemlpsa.difference.plotmlpsa.distribution.plotmlpsa.logisticpsrangetree.plot

Dependencies:clicodetoolscoincolorspacefansifarverggplot2glueGPArotationgtableisobandlabelinglatticelibcoinlifecyclemagrittrMASSMatrixmatrixStatsmgcvmnormtmodeltoolsmultcompmunsellmvtnormnlmepartypillarpkgconfigplyrPSAgraphicspsychR6RColorBrewerRcppreshaperlangrpartsandwichscalesstrucchangesurvivalTH.datatibbleutf8vctrsviridisLitewithrxtablezoo

Readme and manuals

Help Manual

Help pageTopics
Multilevel Propensity Score AnalysismultilevelPSA-package multilevelPSA
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.align.plots
Returns the overall effects as a data frame.as.data.frame.covariate.balance
Estimate covariate effect sizes before and after propensity score adjustment.covariate.balance
Calculate covariate effect size differences before and after stratification.covariateBalance
Transformation of Factors to Individual Levelscv.trans.psa
This function produces a ggplot2 figure containing the mean differences for each level two, or cluster.difftable.plot
Returns a data frame with two columns corresponding to the level 2 variable and the fitted value from the logistic regression.getPropensityScores
Returns a data frame with two columns corresponding to the level 2 variable and the leaves from the conditional inference trees.getStrata
Returns true if the object is of type 'mlpsa'is.mlpsa
Loess plot with density distributions for propensity scores and outcomes on top and right, respectively.loess.plot
Nicer list of objects in memory. Particularly useful for analysis of large data. <#%20http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session>lsos
Returns a heat map graphic representing missingness of variables grouped by the given grouping vector.missing.plot
This function will perform phase II of the multilevel propensity score analysis.mlpsa
Plots the results of a multilevel propensity score model.mlpsa.circ.plot
Estimates propensity scores using the recursive partitioning in a conditional inference framework.mlpsa.ctree
Creates a graphic summarizing the differences between treatment and comparison groups within and across level two clusters.mlpsa.difference.plot
Plots distribution for either the treatment or comparison group.mlpsa.distribution.plot
Estimates propensity scores using logistic regression.mlpsa.logistic
Mapping of variables in 'pisana' with full descriptions.pisa.colnames
Data frame mapping PISA countries to their three letter abbreviation.pisa.countries
Character vector representing the list of covariates used for estimating propensity scores.pisa.psa.cols
North American (i.e. Canada, Mexico, and United States) student results of the 2009 Programme of International Student Assessment.pisana
Multiple covariate balance assessment plot.plot.covariate.balance
Plots the results of a multilevel propensity score model.plot.mlpsa
Plots densities and ranges for the propensity scores.plot.psrange
Prints the overall effects before and after propensity score adjustment.print.covariate.balance
Prints basic information about a 'mlpsa' class.print.mlpsa
Prints information about a psrange result.print.psrange
Prints the results of 'mlpsa' and 'xtable.mlpsa'.print.xmlpsa
Estimates models with increasing number of comparison subjects starting from 1:1 to using all available comparison group subjects.psrange
Provides a summary of a 'mlpsa' class.summary.mlpsa
Prints the summary results of psrange.summary.psrange
Heat map representing variables used in a conditional inference tree across level 2 variables.tree.plot
Prints the results of 'mlpsa' as a LaTeX table.xtable.mlpsa