Domain-Specific Resources

Field Guides

These guides provide applied researchers with curated lists of tutorials, case studies, and resources which contain Stan implementations of the most commonly used models in their domain. If you would like to contribute one for your field, see this Discourse post: Fostering Stan user communities through domain-specific resource pages

Education Research Using Stan

  • Topics: Item Response Theory, Cognitive Diagnosis Models, Multilevel Modeling
  • Maintainer: Sofia Rabe-Hesketh

Stan for Ecology

  • Topics: Ecological times series models, population models, predator-prey dynamics, species site-occupancy models.
  • Maintainer: Vianey Leos Barajas

Stan for Epidemiology

  • Topics: Disease transmission (SIR models), disease mapping (ICAR, BYM models), survival analysis, longitudinal data.
  • Maintainer: Léo Grinsztajn

Stan for Cognitive Science

  • Cognitive Science and Neuroscience papers which use Stan, BRMS, or RStanArm.
  • Maintainer: Bruno Nicenboim

StanConnect Sessions

StanConnect is a virtual miniseries which consists of 3-hour meetings/mini-symposia where each meeting is like “session” of an organized conference. This series was started in 2021 and reprised in 2022. Future StanConnect series will be announced on Discourse.

Stan Through Space and Time (2022)

A half-day event showcasing the use of Stan in spatial statistics and for modeling time series data.

  • Date: October 31, 2022
  • GitHub repository of slides and materials: https://github.com/stan-dev/connect22-space-time
  • Program:
    • Time and tide wait for no one: spatio-temporal modelling in river networks - Edgar Santos Fernandez
    • Spatio-temporal modelling of mosquitoes vector and its environmental drivers in Hong Kong - Stan Yip
    • Robust non-Gaussian models and how to fit them in Stan - Rafael Cabral
    • A space-time extension of the Poisson auto-regression to model Covid-19 cases at the England local authorities level - Pierfrancesco Alaimo Di Loro
    • Fitting spatio-temporal geostatistical models in Stan using the bmstdr R package - Sujit Sahu
    • tipsae: Tools for Handling Indices and Proportions in Small Area Estimation - Silvia De Nicolo
    • geostan: An R package for Bayesian spatial analysis - Connor Donegan
    • Structure induced by a multiple membership transformation on the conditional autoregressive model - Marco Gramatica
    • A Bayesian hierarchical model for disease mapping that accounts for scaling and heavy-tailed latent effects - Victoire Michal
    • Bayesian latent spatial autoregressive growth modeling - Zachary Roman
  • Abstracts
  • Organizer: James Hogg

Cognitive Science and Neuroscience (2021)

  • Date: November 19, 2021
  • Recorded Talks: YouTube
  • Program:
    • Resolving the multiple testing issue in neuroimaging through Bayesian multilevel modeling - Gang Chen
    • Implementation of the Diffusion Decision Model with Across-Trial Variability in the Drift Rate - Kendal Foster and Henrik Singmann
    • It’s complicated: Some observations on the nuanced constraints of the multivariate normal in high dimensions - Mike Lawrence
    • Using computational modeling parameters to measure working memory processes - Jan Göttmann
  • Abstracts
  • Organizer: Bruno Nicenboim

Biostats (2021)

Ecology, models for biological survey data (2021)

A 2-day event showcasing applications of Stan for ecological analyses

  • Day 1: September 30, 2021
  • Day 1 Recorded Talks: YouTube
  • Program Day 1:
    • Using Stan to build better community - Ara Winter
    • Using Stan to diagnose and fit high-dimensional multispecies abundance models - Harold Eyster
    • 250000 parameters: the story of an occupancy model for Colombia’s birdlife in Stan - Jacob Socolar
    • MLOps in a Bayesian workflow: tracking experiments with MLFlow - Maxwell Joseph
  • Day 2: October 4, 2021
  • Program Day 2:
  • Day 2 Recorded Talks: YouTube
    • Evolution of habitat use and coexistence under intraguild predation: a principled Bayesian approach - Josh Goldberg
    • Drift algae controls the consumption of kelp: using data from in-situ subtidal experimentation and ordinary differential equations to mechanistically model the sea urchin behavioral switch - Zach Randell
    • Linking the SPDE method with Stan - Joaquin Cavieres
    • Using Stan to characterize large-scale morphological change in North American birds - Casey Youngflesh
    • Fitting hidden Markov models to ecological time series data in Stan - Vianey Leos Barajas
  • Organizer: Jacob B. Socolar, Cornell Lab of Ornithology
  • Panelist Day 1: Vianey Leos Barajas: Assistant Professor, University of Toronto, Department of Statistical Sciences
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