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mlumr: Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons

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, count, and time-to-event (survival) outcomes via 'Stan', including parametric and flexible M-spline survival baselines. Also provides a one-arm simulated treatment comparison (STC) via comparator-population 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 uses familiar names for data setup, integration and effect summaries, but ML-NMR and ML-UMR specifications and fitted objects are not interchangeable because their evidence structures and models differ.

Version: 0.2.0
Depends: R (≥ 4.1.0)
Imports: methods, stats, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), rstantools (≥ 2.3.0), randtoolbox, survival (≥ 3.1-0), splines2 (≥ 0.4.1), ggplot2 (≥ 3.4.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: testthat (≥ 3.2.0), ggsurvfit, knitr, rmarkdown, posterior, bayesplot, loo, Matrix, cmdstanr, withr, flexsurv, detectseparation, xfun, R.rsp
Published: 2026-10-13
DOI: 10.32614/CRAN.package.mlumr
Author: Ahmad Sofi-Mahmudi ORCID iD [aut, cre], Conor Chandler ORCID iD [aut]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi at gmail.com>
BugReports: https://github.com/choxos/mlumr/issues
License: GPL-3
URL: https://github.com/choxos/mlumr, https://choxos.github.io/mlumr/
NeedsCompilation: yes
SystemRequirements: GNU make
Additional_repositories: https://mc-stan.org/r-packages
Citation: mlumr citation info
Materials: NEWS
In views: MetaAnalysis
CRAN checks: mlumr results

Documentation:

Reference manual: mlumr.html , mlumr.pdf
Vignettes: Preparing data and integration points (source, R code)
Introduction to mlumr (source, R code)
Binary outcomes: an unanchored PASI 75 comparison (source)
Choosing a method for single-arm indirect comparisons: ML-UMR, STC, and naive (source)
Continuous outcomes: an unanchored mean-difference comparison (source)
Count outcomes: an unanchored rate-ratio comparison (source)
Fitting, priors, and diagnostics (source)
Aggregate subgroup information for the relaxed model (source)
Survival (time-to-event) outcomes (source)

Downloads:

Package source: mlumr_0.2.0.tar.gz
Windows binaries: r-devel: mlumr_0.1.0.zip, r-release: mlumr_0.2.0.zip, r-oldrel: mlumr_0.2.0.zip
macOS binaries: r-release (arm64): mlumr_0.2.0.tgz, r-oldrel (arm64): mlumr_0.2.0.tgz, r-release (x86_64): mlumr_0.2.0.tgz, r-oldrel (x86_64): mlumr_0.2.0.tgz
Old sources: mlumr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mlumr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.