David Phillippo
@dmphillippo.bsky.social
Statistician at University of Bristol | Bayesian, meta-analysis and evidence synthesis, #rstats
R for Health Technology Assessment - new book out today!
Free online version gianluca.statistica.it/books/online...
Free online version gianluca.statistica.it/books/online...
R for Health Technology Assessment
gianluca.statistica.it
June 30, 2025 at 2:52 PM
R for Health Technology Assessment - new book out today!
Free online version gianluca.statistica.it/books/online...
Free online version gianluca.statistica.it/books/online...
📣 multinma update v0.7.1 on CRAN * New marginal_effects() function for computing marginal relative effects
* Progress bars for long operations
* trt_ref argument to predict() has been renamed to baseline_ref for consistency
* Bug fixes Full details 👉https://t.co/abYabQCvKS
* Progress bars for long operations
* trt_ref argument to predict() has been renamed to baseline_ref for consistency
* Bug fixes Full details 👉https://t.co/abYabQCvKS
June 17, 2025 at 1:28 PM
📣 multinma update v0.7.1 on CRAN * New marginal_effects() function for computing marginal relative effects
* Progress bars for long operations
* trt_ref argument to predict() has been renamed to baseline_ref for consistency
* Bug fixes Full details 👉https://t.co/abYabQCvKS
* Progress bars for long operations
* trt_ref argument to predict() has been renamed to baseline_ref for consistency
* Bug fixes Full details 👉https://t.co/abYabQCvKS
multinma is back on CRAN 🎉
Stan has been patched to fix the memory allocation bug
This release (v0.6.1) also includes a bugfix for piecewise exponential hazards models - changelog here 👉
https://t.co/abYabQCvKS
Binaries will be built by CRAN over the next few days https://t.co/4UHJPzfgig
Stan has been patched to fix the memory allocation bug
This release (v0.6.1) also includes a bugfix for piecewise exponential hazards models - changelog here 👉
https://t.co/abYabQCvKS
Binaries will be built by CRAN over the next few days https://t.co/4UHJPzfgig
PSA: multinma is temporarily unavailable from CRAN
A small memory allocation bug in Stan tripped some additional CRAN checks, which needs to be patched by rstan.
multinma is still fully functional and passes all tests. In the meantime:
A small memory allocation bug in Stan tripped some additional CRAN checks, which needs to be patched by rstan.
multinma is still fully functional and passes all tests. In the meantime:
June 17, 2025 at 1:27 PM
multinma is back on CRAN 🎉
Stan has been patched to fix the memory allocation bug
This release (v0.6.1) also includes a bugfix for piecewise exponential hazards models - changelog here 👉
https://t.co/abYabQCvKS
Binaries will be built by CRAN over the next few days https://t.co/4UHJPzfgig
Stan has been patched to fix the memory allocation bug
This release (v0.6.1) also includes a bugfix for piecewise exponential hazards models - changelog here 👉
https://t.co/abYabQCvKS
Binaries will be built by CRAN over the next few days https://t.co/4UHJPzfgig
📣multinma v0.6.0 update on CRAN
Major new features (details below):
- Survival analysis
- Automatic integration convergence checking (faster models!)
Plus other improvements and bugfixes
Full changelog 👉https://dmphillippo.github.io/multinma/news/
Major new features (details below):
- Survival analysis
- Automatic integration convergence checking (faster models!)
Plus other improvements and bugfixes
Full changelog 👉https://dmphillippo.github.io/multinma/news/
Changelog
dmphillippo.github.io
June 17, 2025 at 1:27 PM
📣multinma v0.6.0 update on CRAN
Major new features (details below):
- Survival analysis
- Automatic integration convergence checking (faster models!)
Plus other improvements and bugfixes
Full changelog 👉https://dmphillippo.github.io/multinma/news/
Major new features (details below):
- Survival analysis
- Automatic integration convergence checking (faster models!)
Plus other improvements and bugfixes
Full changelog 👉https://dmphillippo.github.io/multinma/news/
Survival analysis with multilevel network meta-regression? Yes please! New preprint extending ML-NMR to likelihoods of any form, including for survival analysis. Accompanied by a new multinma release v0.6.0, which is on CRAN now. https://arxiv.org/abs/2401.12640
June 17, 2025 at 1:27 PM
Survival analysis with multilevel network meta-regression? Yes please! New preprint extending ML-NMR to likelihoods of any form, including for survival analysis. Accompanied by a new multinma release v0.6.0, which is on CRAN now. https://arxiv.org/abs/2401.12640
📣 multinma update 0.4.2 is on CRAN
Fixes a couple of bugs when trials have repeated arms of the same treatment 🐙
✅ get_nodesplits() for node-splitting no longer errors
✅ printing the network now shows the repeated arms
Details 👉 https://dmphillippo.github.io/multinma/news/index.html
Fixes a couple of bugs when trials have repeated arms of the same treatment 🐙
✅ get_nodesplits() for node-splitting no longer errors
✅ printing the network now shows the repeated arms
Details 👉 https://dmphillippo.github.io/multinma/news/index.html
Changelog
dmphillippo.github.io
June 17, 2025 at 1:27 PM
📣 multinma update 0.4.2 is on CRAN
Fixes a couple of bugs when trials have repeated arms of the same treatment 🐙
✅ get_nodesplits() for node-splitting no longer errors
✅ printing the network now shows the repeated arms
Details 👉 https://dmphillippo.github.io/multinma/news/index.html
Fixes a couple of bugs when trials have repeated arms of the same treatment 🐙
✅ get_nodesplits() for node-splitting no longer errors
✅ printing the network now shows the repeated arms
Details 👉 https://dmphillippo.github.io/multinma/news/index.html
📣 Bugfix update multinma 0.4.1 rolling out on CRAN
Fixes an issue introduced with tidyr 1.2.0 that broke ordered multinomial models
Details 👉 https://dmphillippo.github.io/multinma/news
Fixes an issue introduced with tidyr 1.2.0 that broke ordered multinomial models
Details 👉 https://dmphillippo.github.io/multinma/news
Changelog
dmphillippo.github.io
June 17, 2025 at 1:27 PM
📣 Bugfix update multinma 0.4.1 rolling out on CRAN
Fixes an issue introduced with tidyr 1.2.0 that broke ordered multinomial models
Details 👉 https://dmphillippo.github.io/multinma/news
Fixes an issue introduced with tidyr 1.2.0 that broke ordered multinomial models
Details 👉 https://dmphillippo.github.io/multinma/news
📣 Update to multinma v0.4.0 on CRAN
- Node-splitting for checking inconsistency
- Predictive distributions for random effects models
- Improved handling of correlations for integration points (ML-NMR models)
- And more! Details 👉 https://dmphillippo.github.io/multinma/news
#rstats #metaanalysis
- Node-splitting for checking inconsistency
- Predictive distributions for random effects models
- Improved handling of correlations for integration points (ML-NMR models)
- And more! Details 👉 https://dmphillippo.github.io/multinma/news
#rstats #metaanalysis
June 17, 2025 at 1:27 PM
📣 Update to multinma v0.4.0 on CRAN
- Node-splitting for checking inconsistency
- Predictive distributions for random effects models
- Improved handling of correlations for integration points (ML-NMR models)
- And more! Details 👉 https://dmphillippo.github.io/multinma/news
#rstats #metaanalysis
- Node-splitting for checking inconsistency
- Predictive distributions for random effects models
- Improved handling of correlations for integration points (ML-NMR models)
- And more! Details 👉 https://dmphillippo.github.io/multinma/news
#rstats #metaanalysis
Booking now open for our network meta-analysis course 👇 https://x.com/sdias_stats/status/1486706844466827267
June 17, 2025 at 1:27 PM
Booking now open for our network meta-analysis course 👇 https://x.com/sdias_stats/status/1486706844466827267
PhD opportunity in Glasgow - still time to apply!
Predictors of early trial termination using individual-level participant data and aggregate-level data from multiple trials
Co-supervised by myself, advisory team includes @sdias_stats and @WeltonNicky
https://t.co/h4USGbeADd
Predictors of early trial termination using individual-level participant data and aggregate-level data from multiple trials
Co-supervised by myself, advisory team includes @sdias_stats and @WeltonNicky
https://t.co/h4USGbeADd
June 17, 2025 at 1:27 PM
PhD opportunity in Glasgow - still time to apply!
Predictors of early trial termination using individual-level participant data and aggregate-level data from multiple trials
Co-supervised by myself, advisory team includes @sdias_stats and @WeltonNicky
https://t.co/h4USGbeADd
Predictors of early trial termination using individual-level participant data and aggregate-level data from multiple trials
Co-supervised by myself, advisory team includes @sdias_stats and @WeltonNicky
https://t.co/h4USGbeADd
📣Update to multinma (v0.3.0) now on CRAN
- New features for flexibly specifying baseline distributions when producing absolute predictions
- Squashes bugs when specifying certain types of models with contrast data
Full details: https://dmphillippo.github.io/multinma/news/
#rstats #metaanalysis
- New features for flexibly specifying baseline distributions when producing absolute predictions
- Squashes bugs when specifying certain types of models with contrast data
Full details: https://dmphillippo.github.io/multinma/news/
#rstats #metaanalysis
Changelog
dmphillippo.github.io
June 17, 2025 at 1:26 PM
📣Update to multinma (v0.3.0) now on CRAN
- New features for flexibly specifying baseline distributions when producing absolute predictions
- Squashes bugs when specifying certain types of models with contrast data
Full details: https://dmphillippo.github.io/multinma/news/
#rstats #metaanalysis
- New features for flexibly specifying baseline distributions when producing absolute predictions
- Squashes bugs when specifying certain types of models with contrast data
Full details: https://dmphillippo.github.io/multinma/news/
#rstats #metaanalysis
Looking forward to speaking at @HERC_Oxford this Wednesday - details and registration at the link below https://x.com/HERC_Oxford/status/1373967203851251715
June 17, 2025 at 1:26 PM
Looking forward to speaking at @HERC_Oxford this Wednesday - details and registration at the link below https://x.com/HERC_Oxford/status/1373967203851251715
Enjoyed presenting the {multinma} package at #ESMARConf2021 yesterday - if you missed it the recording is available on YouTube: https://youtu.be/d4ufa__hGbY?t=652
#metaanalysis #rstats https://x.com/eshackathon/status/1352291884941664259
#metaanalysis #rstats https://x.com/eshackathon/status/1352291884941664259
ESMARConf2021 livestream Session 2B - Quantitative Synthesis (NMA)
youtu.be
June 17, 2025 at 1:26 PM
Enjoyed presenting the {multinma} package at #ESMARConf2021 yesterday - if you missed it the recording is available on YouTube: https://youtu.be/d4ufa__hGbY?t=652
#metaanalysis #rstats https://x.com/eshackathon/status/1352291884941664259
#metaanalysis #rstats https://x.com/eshackathon/status/1352291884941664259
Catching up on @cantabile's excellent #ESMARConf2021 talk from earlier this morning, developing NMA reporting toolchains for stakeholders like Cochrane. Great to see {multinma} and {nmathresh} being used in the wild too! https://x.com/eshackathon/status/1352529752419164160
June 17, 2025 at 1:26 PM
Catching up on @cantabile's excellent #ESMARConf2021 talk from earlier this morning, developing NMA reporting toolchains for stakeholders like Cochrane. Great to see {multinma} and {nmathresh} being used in the wild too! https://x.com/eshackathon/status/1352529752419164160
📣Update to multinma (v0.2.1) now on CRAN
- Squashed a couple of bugs
- Improved documentation of available likelihoods and link functions
Details: https://dmphillippo.github.io/multinma/news/
- Squashed a couple of bugs
- Improved documentation of available likelihoods and link functions
Details: https://dmphillippo.github.io/multinma/news/
Changelog
dmphillippo.github.io
June 17, 2025 at 1:26 PM
📣Update to multinma (v0.2.1) now on CRAN
- Squashed a couple of bugs
- Improved documentation of available likelihoods and link functions
Details: https://dmphillippo.github.io/multinma/news/
- Squashed a couple of bugs
- Improved documentation of available likelihoods and link functions
Details: https://dmphillippo.github.io/multinma/news/
📣 Update to multinma (v0.2.0) released
Changes include:
- Models for ordered categorical data + example vignette
- Overview of examples for easier navigation
- Inline data transformations
- Improved efficiency when working with fitted models
Details: https://t.co/abYabQCvKS
Changes include:
- Models for ordered categorical data + example vignette
- Overview of examples for easier navigation
- Inline data transformations
- Improved efficiency when working with fitted models
Details: https://t.co/abYabQCvKS
Changelog
dmphillippo.github.io
June 17, 2025 at 1:26 PM
📣 Update to multinma (v0.2.0) released
Changes include:
- Models for ordered categorical data + example vignette
- Overview of examples for easier navigation
- Inline data transformations
- Improved efficiency when working with fitted models
Details: https://t.co/abYabQCvKS
Changes include:
- Models for ordered categorical data + example vignette
- Overview of examples for easier navigation
- Inline data transformations
- Improved efficiency when working with fitted models
Details: https://t.co/abYabQCvKS
The {multinma} R package now has a website!
👉 https://dmphillippo.github.io/multinma/ 👈 - All documentation with illustrated code
- Walkthroughs of example analyses #rstats #metaanalysis
👉 https://dmphillippo.github.io/multinma/ 👈 - All documentation with illustrated code
- Walkthroughs of example analyses #rstats #metaanalysis
June 17, 2025 at 1:26 PM
The {multinma} R package now has a website!
👉 https://dmphillippo.github.io/multinma/ 👈 - All documentation with illustrated code
- Walkthroughs of example analyses #rstats #metaanalysis
👉 https://dmphillippo.github.io/multinma/ 👈 - All documentation with illustrated code
- Walkthroughs of example analyses #rstats #metaanalysis
Methods covered include: network meta-analysis, population adjustment, combining observational and randomised evidence, multiple outcomes, surrogate outcomes, survival outcomes, reliability of recommendations, and comparative efficacy of diagnostic tests https://t.co/QqzaU1ilBp
June 17, 2025 at 1:26 PM
Methods covered include: network meta-analysis, population adjustment, combining observational and randomised evidence, multiple outcomes, surrogate outcomes, survival outcomes, reliability of recommendations, and comparative efficacy of diagnostic tests https://t.co/QqzaU1ilBp
📣 New paper! #openaccess Comparing the performance of population adjustment methods (MAIC, STC, and multilevel network meta-regression) in an extensive simulation study https://onlinelibrary.wiley.com/doi/10.1002/sim.8759
June 17, 2025 at 1:26 PM
📣 New paper! #openaccess Comparing the performance of population adjustment methods (MAIC, STC, and multilevel network meta-regression) in an extensive simulation study https://onlinelibrary.wiley.com/doi/10.1002/sim.8759
Very spoilt by my lovely wife with this birthday gift! 🎁 Stunning print from @thomasp85, thank you!
June 17, 2025 at 1:26 PM
Very spoilt by my lovely wife with this birthday gift! 🎁 Stunning print from @thomasp85, thank you!
📣 R package {multinma} is now on CRAN! 📦
Bayesian network meta-analysis and multilevel network meta-regression of individual and aggregate data in @mcmc_stan https://cran.r-project.org/package=multinma #rstats
Bayesian network meta-analysis and multilevel network meta-regression of individual and aggregate data in @mcmc_stan https://cran.r-project.org/package=multinma #rstats
June 17, 2025 at 1:26 PM
📣 R package {multinma} is now on CRAN! 📦
Bayesian network meta-analysis and multilevel network meta-regression of individual and aggregate data in @mcmc_stan https://cran.r-project.org/package=multinma #rstats
Bayesian network meta-analysis and multilevel network meta-regression of individual and aggregate data in @mcmc_stan https://cran.r-project.org/package=multinma #rstats
📣 New paper! #openaccess
Multilevel network meta-regression combines individual patient data and aggregate data in one network, adjusting for differences in effect modifiers between studies, whilst avoiding aggregation bias
https://doi.org/10.1111/rssa.12579
Multilevel network meta-regression combines individual patient data and aggregate data in one network, adjusting for differences in effect modifiers between studies, whilst avoiding aggregation bias
https://doi.org/10.1111/rssa.12579
June 17, 2025 at 1:26 PM
📣 New paper! #openaccess
Multilevel network meta-regression combines individual patient data and aggregate data in one network, adjusting for differences in effect modifiers between studies, whilst avoiding aggregation bias
https://doi.org/10.1111/rssa.12579
Multilevel network meta-regression combines individual patient data and aggregate data in one network, adjusting for differences in effect modifiers between studies, whilst avoiding aggregation bias
https://doi.org/10.1111/rssa.12579
📦 nmathresh version 0.1.5 is now on CRAN - squashing a couple of bugs #rstats
Changelog: https://cran.r-project.org/web/packages/nmathresh/news/news.html
Changelog: https://cran.r-project.org/web/packages/nmathresh/news/news.html
June 17, 2025 at 1:26 PM
📦 nmathresh version 0.1.5 is now on CRAN - squashing a couple of bugs #rstats
Changelog: https://cran.r-project.org/web/packages/nmathresh/news/news.html
Changelog: https://cran.r-project.org/web/packages/nmathresh/news/news.html
Population adjustment methods (including MAIC, STC) are increasingly common in NICE submissions. Watch this video (18 mins) to find out how they work, what assumptions they make, and what the key issues are to be aware of. https://x.com/NICE_DSU/status/1217452627526504448
June 17, 2025 at 1:26 PM
Population adjustment methods (including MAIC, STC) are increasingly common in NICE submissions. Watch this video (18 mins) to find out how they work, what assumptions they make, and what the key issues are to be aware of. https://x.com/NICE_DSU/status/1217452627526504448
Job advert still live - closing date 12th January
Come work with us!
Senior Research Associate in Medical Statistics / Evidence Synthesis. Providing statistical support, training, methods research, as part of the NICE Guidelines Technical Support Unit @BristolUni. Full details: http://bristol.ac.uk/jobs reference ACAD104360
Senior Research Associate in Medical Statistics / Evidence Synthesis. Providing statistical support, training, methods research, as part of the NICE Guidelines Technical Support Unit @BristolUni. Full details: http://bristol.ac.uk/jobs reference ACAD104360
Working at Bristol | Working at Bristol | University of Bristol
bristol.ac.uk
June 17, 2025 at 1:25 PM
Job advert still live - closing date 12th January