Synthetic CATE benchmark (test set)

Source: R/data.R

Test covariates and ground-truth treatment effects accompanying synth_train. Contains only the covariates and the true CATE (tau), mimicking the deployment setting where a fitted CATE model predicts effects for new individuals.

synth_test

Format

A data frame with 250 rows and 6 columns:

x0, x1, x2, x3, x4

Continuous covariates.

tau

True conditional average treatment effect.

References

Künzel, S. R., Sekhon, J. S., Bickel, P. J., & Yu, B. (2019). Metalearners for estimating heterogeneous treatment effects using machine learning. Proceedings of the National Academy of Sciences, 116(10), 4156-4165.

Examples

data(synth_test)
head(synth_test)
#>            x0     x1         x2          x3         x4 tau
#> 1  0.65794747 -3.000  0.5666075  0.78691820 -1.4924478   0
#> 2 -0.04611018 -2.976 -0.8540344  0.99787821  0.8432643   0
#> 3  1.20150369 -2.952  1.0913615  1.20595702  0.9384851   0
#> 4  0.65876612 -2.928 -0.2655173 -0.61914798 -0.2971724   0
#> 5 -0.61335687 -2.904  0.3945495  0.80175465  0.3327213   0
#> 6 -0.45442967 -2.880 -2.2026415 -0.05421241  0.1106744   0