spline_cate: Estimates non-paramteric CATEs using spline regression as...

View source: R/heterogeneous_effects.R

spline_cateR Documentation

Estimates non-paramteric CATEs using spline regression as proposed by Semenova and Chernozhukov (2020) using the crs package.

Description

Estimates non-paramteric CATEs using spline regression as proposed by Semenova and Chernozhukov (2020) using the crs package.

Usage

spline_cate(delta, z, ...)

Arguments

delta

Vector of doubly robust ATE score. E.g obtained as one column of ATE_dml$delta from ATE_dml.

z

Heterogeneity variable(s) vector, matrix or data.frame

...

Pass crs options, otherwise default settings are used

Value

spline_cate object:

model

crs object of the spline regression

fit

Fitted values of the spline regression

se_fit

Robust standard errors of fitted values

ate

Average teratment effect

z

Original heterogeneity variable(s) data.frame

References

  • Semenova, V., & Chernozhukov, V. (2020). Debiased machine learning of conditional average treatment effects and other causal functions. The Econometrics Journal, utaa027, doi: https://doi.org/10.1093/ectj/utaa027


MCKnaus/causalDML documentation built on Aug. 19, 2023, 5:47 p.m.