CHEMIST
Causal Inference with High-Dimensional Error-Prone Covariates and Misclassified Treatments
v0.1.5
·
May 1, 2023
·
GPL-3
Description
We aim to deal with the average treatment effect (ATE), where the data are subject to high-dimensionality and measurement error. This package primarily contains two functions, which are used to generate artificial data and estimate ATE with high-dimensional and error-prone data accommodated.
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