Package: beeca 0.2.0
Alex Przybylski
beeca: Binary Endpoint Estimation with Covariate Adjustment
Performs estimation of marginal treatment effects for binary outcomes when using logistic regression working models with covariate adjustment (see discussions in Magirr et al (2024) <https://osf.io/9mp58/>). Implements the variance estimators of Ge et al (2011) <doi:10.1177/009286151104500409> and Ye et al (2023) <doi:10.1080/24754269.2023.2205802>.
Authors:
beeca_0.2.0.tar.gz
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beeca.pdf |beeca.html✨
beeca/json (API)
NEWS
| # Install 'beeca' in R: |
| install.packages('beeca', repos = c('https://openpharma.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/openpharma/beeca/issues
- ge_macro_trial01 - Output from the Ge et al (2011) SAS macro applied to the trial01 dataset
- margins_trial01 - Output from the Margins SAS macro applied to the trial01 dataset
- trial01 - Example trial dataset 01
- trial02_cdisc - Example CDISC Clinical Trial Dataset in ADaM Format
Last updated 7 days agofrom:4b72c14afc. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 12 2024 |
| R-4.5-win | OK | Nov 12 2024 |
| R-4.5-linux | OK | Nov 12 2024 |
| R-4.4-win | OK | Nov 12 2024 |
| R-4.4-mac | OK | Nov 12 2024 |
| R-4.3-win | OK | Nov 12 2024 |
| R-4.3-mac | OK | Nov 12 2024 |
Exports:apply_contrastaverage_predictionsestimate_varcovget_marginal_effectpredict_counterfactualssanitize_model
Dependencies:clidplyrfansigenericsgluelatticelifecyclemagrittrpillarpkgconfigR6rlangsandwichtibbletidyselectutf8vctrswithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Apply contrast to calculate marginal estimate of treatment effect and corresponding standard error | apply_contrast |
| Average over counterfactual predictions | average_predictions |
| Estimate variance-covariance matrix for marginal estimand based on GLM model | estimate_varcov |
| Output from the Ge et al (2011) SAS macro applied to the trial01 dataset | ge_macro_trial01 |
| Estimate marginal treatment effects using a GLM working model | get_marginal_effect |
| Output from the Margins SAS macro applied to the trial01 dataset | margins_trial01 |
| Predict counterfactual outcomes in GLM models | predict_counterfactuals |
| Example trial dataset 01 | trial01 |
| Example CDISC Clinical Trial Dataset in ADaM Format | trial02_cdisc |
