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mlumr  

Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons
View on CRAN: Click here


Download and install mlumr package within the R console
Install from CRAN:
install.packages("mlumr")

Install from Github:
library("remotes")
install_github("cran/mlumr")

Install by package version:
library("remotes")
install_version("mlumr", "0.1.0")



Attach the package and use:
library("mlumr")
Maintained by
Ahmad Sofi-Mahmudi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-20
Latest Update: 2026-05-20
Description:
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.
How to cite:
Ahmad Sofi-Mahmudi (2026). mlumr: Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons. R package version 0.1.0, https://cran.r-project.org/web/packages/mlumr. Accessed 25 Oct. 2026.
Previous versions and publish date:
(2026-10-13 10:31), 0.1.0 (2026-05-20 10:30)
Other packages that cited mlumr R package
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Complete documentation for mlumr
Functions, R codes and Examples using the mlumr R package
Full mlumr package functions and examples
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