Causal Inference with High-Dimensional Error-Prone Covariates and Misclassified Treatments
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 3
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 67%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing CHEMIST adds 6 packages (1 with compiled code, 8.6 MB of source tarballs). Heaviest: psychTools 3.8 MB, LaplacesDemon 2.0 MB, GPArotation 1.6 MB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.1.5Latest
- 0.1.32023-04-23
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-04-23
- Total releases
- 2 / 3 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.3.1
- Download size
- 15 KB
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