FindIt: Finding Heterogeneous Treatment Effects
Version 1.0

The heterogeneous treatment effect estimation procedure proposed by Imai and Ratkovic (2013). The proposed method is applicable, for example, when selecting a small number of most (or least) efficacious treatments from a large number of alternative treatments as well as when identifying subsets of the population who benefit (or are harmed by) a treatment of interest. The method adapts the Support Vector Machine classifier by placing separate LASSO constraints over the pre-treatment parameters and causal heterogeneity parameters of interest. This allows for the qualitative distinction between causal and other parameters, thereby making the variable selection suitable for the exploration of causal heterogeneity. The package also contains the function, CausalANOVA, which estimates the average marginal interaction effects by a regularized ANOVA as proposed by Egami and Imai (2016+).

Browse man pages Browse package API and functions Browse package files

AuthorNaoki Egami <negami@princeton.edu>, Marc Ratkovic <ratkovic@princeton.edu>, Kosuke Imai <kimai@princeton.edu>,
Date of publication2016-12-31 08:42:19
MaintainerNaoki Egami <negami@princeton.edu>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("FindIt")

Man pages

AMIE: Decomposing the Combination Effect into the AMEs and the...
Carlson: Data from conjoint analysis in Carlson (2015).
CausalANOVA: Estimating the AMEs and AMIEs with the CausalANOVA.
cv.CausalANOVA: Cross validation for the CausalANOVA.
FindIt: FindIt for Estimating Heterogeneous Treatment Effects
FindIt-internal: Internal FindIt functions
GerberGreen: Data from the 1998 New Haven Get-Out-the-Vote Experiment
LaLonde: National Supported Work Study Experimental Data
plot.PredictFindIt: Plot estimated treatment effects or predicted outcomes for...
predict.FindIt: Computing predicted values for each sample in the data.

Functions

AMIE Man page Source code
AMIEFit Man page Source code
Carlson Man page
CausalANOVA Man page Source code
CausalANOVAFit Man page Source code
CoefExtract Man page Source code
CreateANOVAconst Man page Source code
CreateCoef Source code
CreateWeights Man page Man page Source code
CreatelevelIndex Man page Source code
FindIt Man page Source code
GerberGreen Man page
Glsei Man page Source code
LaLonde Man page
Lcombinefunction Man page Source code
PsyConstraintCombine Man page Source code
SVM.func Source code
Zcombinefunction Man page Source code
cv.CausalANOVA Man page Source code
lengthSlack Man page Source code
makeallway Man page Source code
maketwoway Man page Source code
plot.CausalANOVA Man page Source code
plot.PredictFindIt Man page Source code
plot.cv.CausalANOVA Man page Source code
predict.FindIt Man page Source code
rangeCausalANOVAFit Man page Source code
scale.func Source code
scale.func.2 Source code
search.lambda Source code
search.lambda.nocov Source code
stab.CausalANOVA Man page Source code
summary.CausalANOVA Man page Source code
summary.FindIt Man page Source code

Files

src
src/Makevars
src/solve.f
src/inverse.f
NAMESPACE
data
data/LaLonde.rdata
data/Carlson.rdata
data/GerberGreen.rdata
R
R/stab.CausalANOVA.R
R/CreatelevelIndex.R
R/CoefExtract.R
R/CreateCoef.R
R/predict.FindIt.R
R/plot.PredictEffect.R
R/rangeCausalANOVAFit.R
R/AMIEFit.R
R/SVMHet.R
R/Lcombinefunction.R
R/Zcombinefunction.R
R/CausalANOVAFit.R
R/summary.CausalANOVA.R
R/CausalANOVA.R
R/lengthSlack.R
R/plot.CausalANOVA.R
R/summary.FindIt.R
R/AMIE.R
R/PsyConstraintCombine.R
R/CreateWeights.R
R/cv.CausalANOVA.R
R/Glsei.R
R/makeallway.R
R/plot.cv.CausalANOVA.R
R/CreateANOVAconst.R
R/maketwoway.R
MD5
DESCRIPTION
man
man/CausalANOVA.Rd
man/cv.CausalANOVA.Rd
man/FindIt.Rd
man/plot.PredictFindIt.Rd
man/Carlson.Rd
man/FindIt-internal.Rd
man/LaLonde.Rd
man/AMIE.Rd
man/GerberGreen.Rd
man/predict.FindIt.Rd
FindIt documentation built on May 19, 2017, 2:03 p.m.