AteMeVs
0.1.0Average Treatment Effects with Measurement Error and Variable Selection for Confounders
Overview
A recent method proposed by Yi and Chen (2023) doi:10.1177/09622802221146308 is used to estimate the average treatment effects using noisy data containing both measurement error and spurious variables. The package 'AteMeVs' contains a set of functions that provide a step-by-step estimation procedure, including the correction of the measurement error effects, variable selection for building the model used to estimate the propensity scores, and estimation of the average treatment effects. The functions contain multiple options for users to implement, including different ways to correct for the measurement error effects, distinct choices of penalty functions to do variable selection, and various regression models to characterize propensity scores.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 95%
- Return-value docs
- 100%
- References docs
- 100%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2023-09-04
- Total releases
- 1 / 3 yrs
- License
- GPL-2 OSI
- Download size
- 7.0 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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