mlumr
0.1.0Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons
Overview
Bayesian multilevel unanchored meta-regression (ML-UMR) for indirect treatment comparisons using individual patient data (IPD) and aggregate data (AgD). Implements shared prognostic factor assumption (SPFA) and relaxed SPFA models for binary, continuous, and count outcomes via 'Stan'. Also provides simulated treatment comparison (STC) via parametric G-computation and naive unadjusted benchmarks. ML-UMR is an adaptation of the ML-NMR methodology (Phillippo et al. 2020, doi:10.1111/rssa.12579) implemented in the 'multinma' package (GPL-3) to the unanchored two-trial case; the public API deliberately mirrors multinma's so users can move between ML-NMR and ML-UMR with the same workflow.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-07-2913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-07-2712 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-212 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 32%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 1%
Downloads
Repository
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4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/choxos/mlumr on 2026-08-23.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- 0.1.0Latest2026-05-20 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-20
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Additional repositories
- stan-dev.r-universe.dev
- Minimum R
- ≥ 4.1.0
- Download size
- 395 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("mlumr")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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