https://github.com/openpharma/beeca-simulations
Simulations supporting Magirr et al (2024)
https://github.com/openpharma/beeca-simulations
Last synced: about 2 months ago
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Simulations supporting Magirr et al (2024)
- Host: GitHub
- URL: https://github.com/openpharma/beeca-simulations
- Owner: openpharma
- Created: 2024-05-07T14:06:11.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-17T10:39:37.000Z (6 months ago)
- Last Synced: 2025-03-30T15:51:16.178Z (3 months ago)
- Language: R
- Homepage:
- Size: 54.7 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# Simulations supporting paper: *'Estimating the Variance of Covariate-Adjusted Estimators of Average Treatment Effects in Clinical Trials with Binary Endpoints'*, Magirr et al (2024)
This repo contains the reproducible code for simulation results in the paper by [Magirr et al. (2024)](https://osf.io/9mp58/).
Simulations are based on variance estimators as implemented in the [{beeca}](https://github.com/openpharma/beeca) package.
#### Contents
- `R/extreme_scenario.Rmd`: Results for section 4 ('Extreme scenario').
- `R/realistic_scenario.Rmd`: Results for section 4 ('Realistic scenario').
- `R/misspecified_scenario.Rmd`: Results for section 4 ('Model misspecification').
- `R/plot_ge_vs_ye.Rmd`: Results for section 5 ('Assessing conservativeness').
- **R/utils**: Helper functions for simulation machinery.
- `sessionInfo.yaml`: snapshot of R session to aid reproducibility.
#### References
* Ge, Miaomiao, L Kathryn Durham, R Daniel Meyer, Wangang Xie, and Neal Thomas. 2011. "Covariate-Adjusted Difference in Proportions from Clinical Trials Using Logistic Regression and Weighted Risk Differences." *Drug Information Journal: DIJ/Drug Information Association* 45: 481--93.
* Magirr, Dominic, Mark Baillie, Craig Wang, and Alexander Przybylski. 2024. “Estimating the Variance of Covariate-Adjusted Estimators of Average Treatment Effects in Clinical Trials with Binary Endpoints.” OSF. May 16. .
* Przybylski A, Baillie M, Wang C, Magirr D (2024). beeca: Binary Endpoint Estimation with Covariate Adjustment. R package version 0.1.2,
* Ye, Ting, Marlena Bannick, Yanyao Yi, and Jun Shao. 2023. "Robust Variance Estimation for Covariate-Adjusted Unconditional Treatment Effect in Randomized Clinical Trials with Binary Outcomes." *Statistical Theory and Related Fields* 7 (2): 159--63.