Summer 2023 dates: In-person training July 26-27, 2023 9:00am - ~5:00pm EDT
The Environmental Mixtures Workshop is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of environmental mixtures concepts, techniques, and data analysis methods used in health studies.
This two-day intensive workshop will provide a rigorous introduction to multiple different techniques to analyze exposure to mixtures in environmental health. Led by a team of world experts in environmental health, epidemiology and statistics, many of whom have developed their own methods to analyze exposure to mixtures, the workshop will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice. Emphasis will be given to supervised and unsupervised methods. Since the choice of method depends on the research question at hand, the workshop will conclude with a panel discussion on when each method presented is appropriate for use and for which research questions.
By the end of the workshop, participants will be familiar with the following topics:
- Principal Component Analysis (PCA)
- Factor Analysis (FA)
- Clustering
- Variable Selection (Lasso, elastic net)
- Bayesian Kernel (BKMR)
- Weighted Quantile Sum Regression (WQS)
- Emerging mixtures topics and novel extensions
- Tree-based methods
AUDIENCE AND REQUIREMENTS
Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are four requirements to attend this workshop:
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Each participant must have an introductory background in statistics.
- Each participant must be familiar with R.
- Each participant is required to have a personal laptop/computer and a free, basic RStudio Cloud account. All lab sessions will be done using RStudio Cloud.
- Per Columbia University Policy, on-campus participants must be vaccinated and should be prepared to show proof of vaccination while on campus. Any changes to on-campus policies will be updated here and communicated to participants.
ADDITIONAL INFORMATION
