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causalSLSE (version 0.4-1)

Semiparametric Least Squares Inference for Causal Effects

Description

Several causal effects are measured using least squares regressions and basis function approximations. Backward and forward selection methods based on different criteria are used to select the basis functions.

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Version

Install

install.packages('causalSLSE')

Monthly Downloads

167

Version

0.4-1

License

GPL (>= 2)

Maintainer

Pierre Chausse

Last Published

August 29th, 2025

Functions in causalSLSE (0.4-1)

simDat1

Simulated Data
summary

Summary Method for Fitted Models
update

Update Methods
simDat5

Simulated Data
simDat2

Simulated Data
simDat3

Simulated Data
print

Print Methods
selSLSE

Knots Selection Method
slseKnots

Knots Creator for Basis Functions
simDat4

Simulated Data.
predict

Outcome Prediction
as.model

Converter into Model Objects
nsw

Lalonde Subsample of the National Supported Work Demonstration Data (NSW)
plot

Plot of Predicted Outcome
cslseModel

Semiparametric Least Squares Estimator Model
causalSLSE

Causal Effect Based on Semiparametric Least Squares Models
altCausal

Alternative Causal Effect estimation methods.
extract

extract methods for some objects.
estSLSE

Least Squares Estimate of cslseModel or slseModel Objects
llSplines

Local Linear Splines Generator for Model Objects