To cite package ‘mlumr’ in publications use:

  Sofi-Mahmudi A, Chandler C (2026). _mlumr: Multilevel Unanchored
  Meta-Regression for Indirect Treatment Comparisons_. R package
  version 0.1.0. An adaptation of the ML-NMR methodology to the
  unanchored case; built on conventions established by the 'multinma'
  package (Phillippo et al., GPL-3).,
  <https://github.com/choxos/mlumr>.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {mlumr: Multilevel Unanchored Meta-Regression for Indirect Treatment Comparisons},
    author = {Ahmad Sofi-Mahmudi and Conor Chandler},
    year = {2026},
    note = {R package version 0.1.0. An adaptation of the ML-NMR methodology to the unanchored case; built on conventions established by the 'multinma' package (Phillippo et al., GPL-3).},
    url = {https://github.com/choxos/mlumr},
  }

  Phillippo D (2020). _multinma: Bayesian Network Meta-Analysis of
  Individual and Aggregate Data_. doi:10.5281/zenodo.3904454
  <https://doi.org/10.5281/zenodo.3904454>. R package, GPL-3. The
  ML-NMR reference implementation that mlumr adapts to the unanchored
  case., <https://dmphillippo.github.io/multinma/>.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {multinma: Bayesian Network Meta-Analysis of Individual and Aggregate Data},
    author = {David M. Phillippo},
    year = {2020},
    note = {R package, GPL-3. The ML-NMR reference implementation that mlumr adapts to the unanchored case.},
    url = {https://dmphillippo.github.io/multinma/},
    doi = {10.5281/zenodo.3904454},
  }

  Chandler C, Ishak J (2025). “Anchors Away: Navigating Unanchored
  Indirect Comparisons With Multilevel Unanchored Meta-Regression
  (ML-UMR).” _Value in Health_, *28*, S498. ISPOR Europe 2025 poster,
  MSR28,
  <https://www.valueinhealthjournal.com/article/S1098-3015(25)05944-3/abstract>.

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Anchors Away: Navigating Unanchored Indirect Comparisons With Multilevel Unanchored Meta-Regression (ML-UMR)},
    author = {Conor Chandler and Jack Ishak},
    journal = {Value in Health},
    year = {2025},
    volume = {28},
    pages = {S498},
    note = {ISPOR Europe 2025 poster, MSR28},
    url = {https://www.valueinhealthjournal.com/article/S1098-3015(25)05944-3/abstract},
  }

  Chandler C, Ishak J (2026). “Surviving Unanchored Indirect
  Comparisons: An Extension of Multilevel Unanchored Meta-Regression
  (ML-UMR) for Survival Analyses.” _Value in Health_, *29*(S6). ISPOR
  2026 poster, MSR131,
  <https://www.ispor.org/heor-resources/presentations-database/presentation-cti/ispor-2026/poster-session-3-3/surviving-unanchored-indirect-comparisons-an-extension-of-multilevel-unanchored-meta-regression-ml-umr-for-survival-analyses>.

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Surviving Unanchored Indirect Comparisons: An Extension of Multilevel Unanchored Meta-Regression (ML-UMR) for Survival Analyses},
    author = {Conor Chandler and Jack Ishak},
    journal = {Value in Health},
    year = {2026},
    volume = {29},
    number = {S6},
    note = {ISPOR 2026 poster, MSR131},
    url = {https://www.ispor.org/heor-resources/presentations-database/presentation-cti/ispor-2026/poster-session-3-3/surviving-unanchored-indirect-comparisons-an-extension-of-multilevel-unanchored-meta-regression-ml-umr-for-survival-analyses},
  }

  Phillippo D, Dias S, Ades A, Belger M, Brnabic A, Schacht A, Saure D,
  Kadziola Z, Welton N (2020). “Multilevel Network Meta-Regression for
  population-adjusted treatment comparisons.” _Journal of the Royal
  Statistical Society: Series A_, *183*(3), 1189-1210.
  doi:10.1111/rssa.12579 <https://doi.org/10.1111/rssa.12579>.

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Multilevel Network Meta-Regression for population-adjusted treatment comparisons},
    author = {David M. Phillippo and Sofia Dias and A. E. Ades and Mark Belger and Alan Brnabic and Alexander Schacht and Daniel Saure and Zbigniew Kadziola and Nicky J. Welton},
    journal = {Journal of the Royal Statistical Society: Series A},
    year = {2020},
    volume = {183},
    number = {3},
    pages = {1189--1210},
    doi = {10.1111/rssa.12579},
  }