Why is it that more shark attacks occur when more ice cream is sold? The answer: both are related to the weather, here an unmeasured confounder.
{causens} is an R package that will allow to perform various sensitivity analysis methods to adjust for unmeasured confounding within the context of causal inference. Currently, we provide the following methods:
install.packages("devtools")
library(devtools)
devtools::install_github("Kuan-Liu-Lab/causens")
library(causens)
library(causens)
# Simulate data
data <- simulate_data(N = 10000, seed = 123, alpha_uz = 1,
beta_uy = 1, treatment_effects = 1)
# Treatment model is incorrect since U is "missing"
causens_sf(Z ~ X.1 + X.2 + X.3, "Y", data = data, c1 = 0.25, c0 = 0.25)$estimated_ate
Please cite our software using:
@Manual{,
title = {causens: Perform Causal Sensitivity Analyses Using Various Statistical Methods},
author = {Larry Dong and Yushu Zou and Kuan Liu},
year = {2024},
note = {R package version 0.0.3, https://github.com/Kuan-Liu-Lab/causens},
url = {https://kuan-liu-lab.github.io/causens/},
}
Please report bugs by opening an issue. If you have a question regarding the usage of causens, please open a discussion. If you would like to contribute to the package, please open a pull request.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4