Overview | Methods | Primary analysis (placebo-controlled phase) | OLE phase analysis (open-label extension) | Simulation | Getting help | Quick start | References
This package is hidden from search results because it is not hosted in the universe of the upstream owner
cran. To fix this you can add URL: https://cran.r-universe.dev/rdborrow to the package DESCRIPTION file. See also theR-universe documentation.Package: rdborrow 0.0.5.1
Matt Secrest
rdborrow: External Control Borrowing for Rare Disease Trials
Implements causal inference methods for incorporating external control data into randomized controlled trials (RCTs) with longitudinal outcomes. Provides an analysis module supporting weighting-based methods such as inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW), difference-in-differences (DID), and synthetic control approaches for borrowing external control information, as well as a simulation module for generating trial and external control data, evaluating estimator performance via Monte Carlo studies, and conducting power analyses for sample size determination. Methods are based on Zhou et al. (2025) <doi:10.1093/jrsssa/qnae075> and Zhou et al. (2024) <doi:10.1080/10543406.2024.2330209>.
Authors:
rdborrow_0.0.5.1.tar.gz
rdborrow_0.0.5.1.zip(r-4.7-any)rdborrow_0.0.5.1.zip(r-4.6-any)
rdborrow_0.0.5.1.tar.gz(r-4.7-any)rdborrow_0.0.5.1.tar.gz(r-4.6-any)
rdborrow_0.0.5.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rdborrow/json (API)
| # Install 'rdborrow' in R: |
| install.packages('rdborrow', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/genentech/rdborrow/issues
Pkgdown/docs site:https://genentech.github.io
Datasets:
- SyntheticData - Synthetic example dataset for rdborrow
- SyntheticDataII - Unbalanced synthetic example dataset for rdborrow
Last updated from:b073b4cd11. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 225 | ||
| source / vignettes | OK | 315 | ||
| linux-release | OK | 241 | ||
| windows-devel | OK | 190 | ||
| windows-release | OK | 196 | ||
| wasm-release | OK | 139 |
Exports:did_ec_aipwdid_ec_ipwdid_ec_orec_aipwec_ipwestimaterun_analysisrun_simulationscmsetup_analysis_OLEsetup_analysis_primarysetup_bootstrapsetup_method_DIDsetup_method_SCMsetup_method_weightingsetup_simulation_OLEsetup_simulation_primarysimulate_outcome_from_modelsimulate_trialsimulate_trial_statussimulate_trt_assignsimulate_X_copulasimulate_X_dct_mvnormsimulate_X_mixture
Dependencies:ADGofTestbackportsbootcheckmateclarabelcliclustercolorspacecopulacrayonCVXRECOSolveRformatRfutile.loggerfutile.optionsgluegmpgslhighshmslambda.rlatticelifecycleMatrixmvtnormnumDerivosqppcaPPpkgconfigprettyunitsprogresspsplineR6RcppRcppEigenrlangS7scsslamstabledistvctrs
Introduction to rdborrow
Last update: 2026-10-08
Started: 2026-08-31
OLE Analysis Workflow
OLE phase | 1 DID methods | 1.1 DID-EC-IPW | 1.2 DID-EC-AIPW | 1.3 DID-EC-OR | 2 Synthetic control method | References
Last update: 2026-10-08
Started: 2026-08-31
Primary Analysis Workflow
Primary analysis | 1 Load data | 2 EC-IPW | 2.1 No borrowing (weight = 0) | 2.2 Optimal weight (data-adaptive) | 2.3 Bootstrap inference | 3 EC-AIPW | 3.1 No borrowing (weight = 0) | 3.2 Optimal weight (data-adaptive) | 3.3 Bootstrap inference | 4 Notes | References
Last update: 2026-10-08
Started: 2026-08-31
Simulation Workflow for Primary Analysis
Primary analysis | 1 Simulate a list of datasets for primary analysis | 1.1 Create basic setup | 1.2 Generate simulation data list for null hypothesis | 1.3 Generate simulation data list for alternative hypothesis | 2 Parametric inference | 3 Bootstrap inference | References
Last update: 2026-10-08
Started: 2026-08-31
Simulation Workflow for OLE Phase
OLE study | 1. Simulate a dataset for OLE study | 2 Bootstrap inference | References
Last update: 2026-09-24
Started: 2026-08-31
