Package: sampleSelection 1.2-15

Arne Henningsen

sampleSelection: Sample Selection Models

Two-step and maximum likelihood estimation of Heckman-type sample selection models: standard sample selection models (Tobit-2), endogenous switching regression models (Tobit-5), sample selection models with binary dependent outcome variable, interval regression with sample selection (only ML estimation), and endogenous treatment effects models. These methods are described in the three vignettes that are included in this package and in econometric textbooks such as Greene (2011, Econometric Analysis, 7th edition, Pearson).

Authors:Arne Henningsen [aut, cre], Ott Toomet [aut], Sebastian Petersen [ctb]

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manual.pdf |manual.html✨
card.svg |card.png
sampleSelection/json (API)
NEWS

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

Bug tracker:https://r-forge.r-project.org/projects/sampleselection

Datasets:
  • Mroz87 - U.S. Women's Labor Force Participation
  • nlswork - National Longitudinal Survey of Young Working Women
  • RandHIE - RAND Health Insurance Experiment
  • Smoke - Survey Responses on Smoking Behaviour

On CRAN:

Conda:

8.53 score 5 packages 421 scripts 9.0k downloads 2 mentions 14 exports 76 dependencies

Last updated from:b54bd53621. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK206
source / vignettesOK333
linux-release-x86_64OK197
macos-release-arm64OK130
macos-oldrel-arm64OK118
windows-develOK167
windows-releaseOK170
windows-oldrelOK152
wasm-releaseOK118

Exports:binaryChoiceheckitheckit2fitheckit5fitheckitTfitheckitVcovinvMillsRatiolinearPredictorsprobitselectiontobit2Bfittobit2fittobit5fittreatReg

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdigestdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselecttimeDateurcautf8vctrsVGAMviridisLitewithrzoo

Interval Regression with Sample Selection

Rendered fromintReg.Rnwusingutils::Sweaveon May 21 2026.

Last update: 2017-12-07
Started: 2017-10-22

Sample Selection Models

Rendered fromselection.Rnwusingutils::Sweaveon May 21 2026.

Last update: 2026-01-19
Started: 2011-11-12

Using treatReg

Rendered fromtreatReg.Rnwusingutils::Sweaveon May 21 2026.

Last update: 2019-07-15
Started: 2015-02-01

Readme and manuals

Help Manual

Help pageTopics
Extract Coefficients from Selection Modelscoef.selection coef.summary.selection print.coef.selection
Fitted Values of Selection Modelsfitted.selection
Heckit Variance Covariance MatrixheckitVcov
Inverse Mill's Ratio of probit modelsinvMillsRatio
Calculates linear predictors for different modelslinearPredictors linearPredictors.probit
Data of Binary Choice Modelsmodel.frame.binaryChoice
Data of Selection Modelsmodel.frame.selection
Design Matrix of Binary Choice Modelsmodel.matrix.binaryChoice
Design Matrix of Selection Modelsmodel.matrix.selection
U.S. Women's Labor Force ParticipationMroz87
National Longitudinal Survey of Young Working Womennlswork
Predict method for fitted probit modelspredict.probit
Predict method for fitted sample selection modelspredict.selection
Binary choice models.binaryChoice probit
probit-methodsfitted.probit logLik.probit nObs.probit nobs.probit print.probit probit-methods
RAND Health Insurance ExperimentRandHIE
Residuals of probit modelsresiduals.probit
Residuals of Selection Modelsresiduals.selection
Heckman-style selection and treatment effect modelsheckit selection treatReg
selection-methodslogLik.selection nObs.selection nobs.selection print.selection selection-methods
Survey Responses on Smoking BehaviourSmoke
Summarizing Probit Estimationsprint.summary.probit summary.probit
Summarizing Selection Estimationsprint.summary.selection summary.selection
Extract Variance Covariance Matrixvcov.selection