CausalFX: Methods for Estimating Causal Effects from Observational Data
Version 1.0.1

Estimate causal effects of one variable on another, currently for binary data only. Methods include instrumental variable bounds, adjustment by a given covariate set, adjustment by an induced covariate set using a variation of the PC algorithm, and an effect bounding method (the Witness Protection Program) based on covariate adjustment with observable independence constraints.

AuthorRicardo Silva [cre, aut], Robin Evans [aut]
Date of publication2015-05-20 17:10:47
MaintainerRicardo Silva <ricardo@stats.ucl.ac.uk>
LicenseGPL (>= 2)
Version1.0.1
URL http://github.com/rbas2015/CausalFX
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("CausalFX")

Popular man pages

covsearch: Search for Causal Effect Covariate Adjustment
print.cfx: Prints a CausalFX Problem Instance
print.summary.covsearch: Print Summaries of Covariate Search Outputs
print.summary.iv: Print Summaries of Binary Instrumental Variable Analyses
simulateWitnessModel: Generates Synthetic CausalFX Problems
synthetizeCausalEffect: Computes Average Causal Effects by Covariate Adjustment in...
wpp: The Witness Protection Program for Causal Effect Estimation
See all...

All man pages Function index File listing

Man pages

bindagCausalEffectBackdoor: Estimates Average Causal Effects by Covariate Adjustment in...
cfx: Creates a CausalFX Problem Instance
covsearch: Search for Causal Effect Covariate Adjustment
iv: Bayesian Analysis of Binary Instrumental Variables
print.cfx: Prints a CausalFX Problem Instance
print.summary.covsearch: Print Summaries of Covariate Search Outputs
print.summary.iv: Print Summaries of Binary Instrumental Variable Analyses
print.summary.wpp: Print Summaries of Witness Protection Program Outputs
simulateWitnessModel: Generates Synthetic CausalFX Problems
summary.covsearch: Summarize Covariate Search Outputs
summary.iv: Summarize Binary Instrumental Variable Analyses
summary.wpp: Summarize Witness Protection Program Outputs
synthetizeCausalEffect: Computes Average Causal Effects by Covariate Adjustment in...
wpp: The Witness Protection Program for Causal Effect Estimation

Functions

binAnalyticalIV Source code
binParamPosteriorExpectation Source code
binParamPosteriorSampling Source code
bindagCausalEffectBackdoor Man page Source code
bindagMonteCarloCausalEffect Source code
buildLppScdd Source code
buildTableParameters Source code
cfx Man page Source code
covariateSearchSummarizeACEs Source code
covsearch Man page Source code
dsep Source code
dtoc Source code
filterAdjustmentSet Source code
getBinDAGModelData Source code
getVEtaStar Source code
inferDep Source code
inferDepBayes Source code
iv Man page Source code
logitDist Source code
patternRepeat Source code
print.cfx Man page Source code
print.summary.covsearch Man page Source code
print.summary.iv Man page Source code
print.summary.wpp Man page Source code
rowMaxs Source code
rowMins Source code
simulateWitnessModel Man page Source code
summary.covsearch Man page Source code
summary.iv Man page Source code
summary.wpp Man page Source code
synthetizeCausalEffect Man page Source code
validateData Source code
wpp Man page Source code
wppIntervalGenerationAnalytical Source code
wppIntervalGenerationNumerical Source code
wppParamPosteriorExpectation Source code
wppPosteriorSampling Source code
wppSummarizeBounds Source code

Files

NAMESPACE
R
R/synthetize.R
R/wpp.R
R/causal_class.R
R/search.R
R/iv.R
R/util.R
MD5
DESCRIPTION
man
man/covsearch.Rd
man/wpp.Rd
man/print.summary.iv.Rd
man/summary.iv.Rd
man/summary.covsearch.Rd
man/print.cfx.Rd
man/print.summary.wpp.Rd
man/print.summary.covsearch.Rd
man/synthetizeCausalEffect.Rd
man/cfx.Rd
man/summary.wpp.Rd
man/bindagCausalEffectBackdoor.Rd
man/iv.Rd
man/simulateWitnessModel.Rd
CausalFX documentation built on May 19, 2017, 4:26 p.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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

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