Olivier Supplisson

the (rather condensed by my standards) slides for my own talk are available here: github.com/sampower88/t...

Just few days left to apply to one of these postdoc positions in my infectious disease modelling Unit at @pasteur.fr in Paris!

Conditional and Marginal Models: Another View There has existed controversy about the use of marginal and conditional models, particularly in the analysis of data from longitudinal studies. We show that alleged differences in the behavior of parameters in so-called marginal and conditional models are based on a failure to compare like with like. In particular, these seemingly apparent differences are meaningless because they are mainly caused by preimposed unidentifiable constraints on the random effects in models. We discuss the advantages of conditional models over marginal models. We regard the conditional model as fundamental, from which marginal predictions can be made.

Perhaps this one and its references can serve as a useful starting point? Youngjo Lee. John A. Nelder. "Conditional and Marginal Models: Another View." Statist. Sci. 19 (2) 219 - 238, May 2004. doi.org/10.1214/0883...

Postdoctoral positions in epidemic mathematical/statistical modelling - Research Job description We are recruiting postdocs to contribute to research projects in the Mathematical Modelling of Infectious Diseases Unit, at Institut Pasteur in Paris. The candidates will be expected t...

New postdoc positions with a number of exciting epidemic modelling projects opening in our Unit at @pasteur.fr in beautiful Paris. Deadline for applications: 26th June.
research.pasteur.fr/en/job/postd...

Starting to look like I might not be able to work at Harvard anymore due to recent funding cuts. If you know of any open statistical consulting positions that support remote work or are NYC-based, please reach out! 😅

link 📈🤖
Wasserstein complexity penalization priors: a new class of penalizing complexity priors (Bolin, Simas, Xiong) Penalizing complexity (PC) priors provide a principled framework for reducing model complexity by penalizing the Kullback--Leibler Divergence (KLD) between a ``simple'' base model

Abstract Introduction A key step in the Bayesian workflow for model building is the graphical assessment of model predictions, whether these are drawn from the prior or posterior predictive distribution. The goal of these assessments is to identify whether the model is a reasonable (and ideally accurate) representation of the domain knowledge and/or observed data. There are many commonly used visual predictive checks which can be misleading if their implicit assumptions do not match the reality. Thus, there is a need for more guidance for selecting, interpreting, and diagnosing appropriate visualizations. As a visual predictive check itself can be viewed as a model fit to data, assessing when this model fails to represent the data is important for drawing well-informed conclusions. Demonstration We present recommendations for appropriate visual predictive checks for observations that are: continuous, discrete, or a mixture of the two. We also discuss diagnostics to aid in the selection of visual methods. Specifically, in the detection of an incorrect assumption of continuously-distributed data: identifying when data is likely to be discrete or contain discrete components, detecting and estimating possible bounds in data, and a diagnostic of the goodness-of-fit to data for density plots made through kernel density estimates. Conclusion We offer recommendations and diagnostic tools to mitigate ad-hoc decision-making in visual predictive checks. These contributions aim to improve the robustness and interpretability of Bayesian model criticism practices.

New paper Säilynoja, Johnson, Martin, and Vehtari, "Recommendations for visual predictive checks in Bayesian workflow" teemusailynoja.github.io/visual-predi... (also arxiv.org/abs/2503.01509)

Stephen Jun Villejo, Sara Martino, Janine Illian, William Ryan, Finn Lindgren
Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration
https://arxiv.org/abs/2502.18962

After a long wait, the working paper for the Many-Economists Project: The Sources of Researcher Variation in Economics. We had 146 teams perform the same research three times, each time with less freedom. What source of freedom leads to different choices and results? papers.ssrn.com/sol3/papers....

Exciting event organised by @mrc-bsu.bsky.social, 5-6 june 2025:

Workshop on Adaptive and Bayesian designs in real trials: clinicians', patients' and statisticians' perspectives

www.mrc-bsu.cam.ac.uk/events/works...

Two postdoc positions to work on virus epi & evolution in response to vaccination, with both theoretical models + data analysis. Paris/Montpellier. With Sylvain Gandon, Sébastien Lion, François Blanquart, Katrina Lythgoe, & Troy Day
emploi.cnrs.fr/Offres/CDD/U...
emploi.cnrs.fr/Offres/CDD/U...

⚠️ Banger alert⚠️

"INLA: past, present, and future. A workshop in honour of Håvard Rue’s 60th birthday."

Don't miss it: lnkd.in/dJDa3x_S
When: 21-23 May 2025
Where: Glasgow

So happy to be able to go there ✌

#StatsSky #Bayesian

Our short course in infectious disease epidemiology and control is now open for applications! I am proud to be the director of this popular hands-on course which will teach you the basics of epidemic modelling in just two weeks! Apply here and spread the word! www.infectiousdiseasemodels.org

If you’ve just arrived on BlueSky and are interested in infectious disease modelling, these starter packs are for you. 👇 I update them regularly, but I am sure I’ve missed many colleagues so don’t hesitate to send suggestions!

Infectious Disease Modelling #IDModelling Join the conversation

Infectious Disease Modelling starter pack update! First pack is full so I created a second one. Pls keep on sending suggestions! (bio should contain experience relevant for this pack)
IDModelling pack 1: go.bsky.app/86Ao1a5
IDModelling pack 2 : go.bsky.app/2oBB7KX

I created a starter pack for simulation-based inference (aka. likelihood-free inference).

Let me know if you’d like me to add you.

go.bsky.app/GVnJRoK

I made a starter-pack for Statistics and Statistics-related groups, departments or organisations. Please share, and suggest accounts that I have missed.
go.bsky.app/q6MfWL

Starter pack of infectious disease modellers from CMMID - the Centre for Mathematical Modelling of Infectious Diseases at LSHTM.
We are 150 in CMMID but just getting started on Bluesky!

go.bsky.app/625gwoG

Personal reflection: "Clinical prediction models & the multiverse of madness"

Thanks to BMC Medicine for 'getting this'

Many reviewers/Eds pushed for writing style & tone changes

This thread delves into this & why we stuck to our original vision

bmcmedicine.biomedcentral.com/articles/10....

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