StanConnect2021: Biomedical Statistics

Dear all,

It is with great pleasure that I announce the realisation of the Biomedical chapter of the StanConnect 2021 series of events.
The goal is to bring together people working in biostatistical applications loosely related to the Stan probabilistic programming language.

The tentatitive titles are:

  • “Coding the BYM2 model for disconnected graphs in Stan or how I stopped worrying and learned to love PC priors” Mitzi Morris (Researcher), Columbia University.

  • “Normalized power prior models in Stan”
    Ethan Alt (PhD student), North Carolina University (Chapel Hill).

  • “Summarising enzyme information from online databases using Stan and Arviz”
    Teddy Groves (Postdoctoral researcher), Technical University of Denmark.

  • “Automated kinetic modelling in Stan and its application to the methionine cycle”
    Nicholas Cowie (PhD student), Technical University of Denmark.

  • “Leveraging external data in Bayesian adaptive platform designs using Stan”
    Alejandra Avalos-Pacheco (Postdoctoral researcher), Harvard Medical School.

  • “A Bayesian Approach to Representing Variability in Space in Cardiac Action Potential Properties”
    Alejandro Nieto Ramos (PhD student), Rochester Institute of Technology.

and @f2harrell will be a discussant, which I think is very exciting!

I have put together a Github repository with talk abstracts.

The event is scheduled to take place virtually via Zoom on 19 October 2021, 10 AM-1PM EST.
Register here.

It’ll be great to see many of you there.


There has been a slight change: Alehandra’s talk will now be replaced by

  • “Using Hidden Markov Models as a complement/alternative to survival models” by @martinmodrak (Researcher), Czech Academy of Sciences.
1 Like