For the problem of indirect treatment comparison with limited subject-level data, this
package provides tools for model-based standardisation with several different computation approaches.
See Remiro‐Azócar A, Heath A, Baio G (2022) "Parametric G‐computation for compatible
indirect treatment comparisons with limited individual patient data",
Res. Synth. Methods, 1–31. ISSN 1759-2879, <doi:10.1002/jrsm.1565>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
boot, cli, copula, crayon, dplyr, ggplot2, glue, pillar, purrr, rlang, rstanarm, stats, stringr, tibble, tidyr, tidyselect, Rdpack (≥ 0.7) |
| Suggests: |
causaldata, doSNOW, gridExtra, here, knitr, maicplus, marginaleffects, MASS, parallel, reshape2, rmarkdown, stdReg2, testthat (≥ 3.0.0) |
| Published: |
2026-01-21 |
| DOI: |
10.32614/CRAN.package.outstandR |
| Author: |
Nathan Green 
 [aut, cre, cph],
Chengyang Gao [aut],
Antonio Remiro-Azocar
[aut] |
| Maintainer: |
Nathan Green <n.green at ucl.ac.uk> |
| BugReports: |
https://github.com/StatisticsHealthEconomics/outstandR/issues/ |
| License: |
GPL (≥ 3) |
| URL: |
https://StatisticsHealthEconomics.github.io/outstandR/ |
| NeedsCompilation: |
no |
| Language: |
en-GB |
| Materials: |
README, NEWS |
| CRAN checks: |
outstandR results |