Non-SOT Event: Bayesian Modeling for Environmental Health Workshop: Concepts and Computational Tools

The Bayesian Modeling for Environmental Health Workshop is a three-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, techniques, and data analysis methods used in Bayesian modeling with applications in Environmental Health.

By the end of the workshop, participants will be familiar with the following topics:
- Principles of Bayesian inference
- Practicalities of Bayesian inference
- Choosing priors
- Different data structures (spatial, point, continuous, categorical)
- Advantages and drawbacks of Bayesian approaches
- Temporal modeling
- Spatial modeling
- Spatio-temporal modeling
- Hierarchical modeling
- Exposure response functions
- Examples of use
- Software options

Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.

Prerequisites and Requirements: There are three requirements to attend this training:
- Basic familiarity with R and R studio (how to download R/R studio, and how to install a package) is recommended to get the most out of the workshop.
- Familiarity with spatial and temporal data structures, as well as exponential family distribution types (normal, Poisson etc.) would also be useful, though not essential.
- Each participant is required to bring a personal laptop as all lab sessions will be done on your personal laptop. Each participant will be using RStudio Cloud to carry out tasks while attending the Workshop.

Capacity is limited. Paid registration is required to attend.

Additional information:
- Website has more details: https://www.publichealth.columbia.edu/academics/non-degree-special-programs/professional-non-degree-programs/skills-health-research-professionals-sharp-training/trainings/bayesian-modeling
- Email us with any questions: Columbia.Bayesian@gmail.com