Environmental Mixtures Workshop
Applications in Environmental Health Studies
Registration is open! Join us for the next in-person Environmental Mixtures Workshop on July 26-27, 2023.
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. Register here.
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Jump to: Overview | Prerequisites | R tutorials | Instructors | Scholarships | Locations | Testimonials | Registration Fees | Additional Information
Mixtures Workshop Overview
Summer 2023 dates: In-person training July 26-27, 2023 9:00am - ~5:00pm EDT
Traditionally, environmental health studies have focused on assessing risks related to a single pollutant at a time. This, however, does not reflect reality, since we are constantly exposed to multiple pollutants at once. Recently, there has been an increased interest in methods that allow researchers to assess exposures to many pollutants at a time. These methods are able to accommodate the high dimension of the exposure matrix, as well as the usually high correlation across exposures of interest.
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)
- 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 three requirements to attend this workshop:
- 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.
Knowing basic R platform and commands is required for the Boot Camp as noted in prerequisites above. This training will use RStudio Cloud. If you are new to R or need a refresher, you can review the below tutorials to be well prepared:
- R Programming Tutorial - Learn the Basics: A free datalab.cc class on R fundamentals
- Once you create your free, basic RStudio Cloud account for the training: Primers on Programming Basics and Visualization Basics.
- SHARP Program RStudio Cloud Tutorial: This self-paced tutorial from the Columbia SHARP Program walks through the Cloud Platform you will use at the training, as well as some basic exercises. We recommend this tutorial if you have not used the Cloud version of RStudio before, or if you are a beginner user of R.
If you have any specific questions about R and R studio in the context of the Environmental Mixtures Workshop, please email us.
Brent Coull, PhD, Harvard T.H. Chan School of Public Health, Harvard University.
Chris Gennings, PhD, Research Professor and Biostatistics Division Director, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai. Dr. Gennings’ research program includes the development of Weighted Quantile Sum (WQS) regression (joint work with a dissertation student), a method that is robust to confounding concerns based on complex correlations among exposure to environmental mixtures. She is currently developing methods for nutritional and environmental exposures that estimate and evaluate regulatory guideline values for mixtures.
Jeff Goldsmith, PhD, Associate Professor, Department of Biostatistics, Columbia University Mailman School of Public Health. Dr. Goldsmith's statistical research focuses on high-dimensional data, with particular emphasis on dimension reduction methods, and modeling health outcomes. In addition to environmental health, he works on physical activity quantification using accelerometers, and on motor control experiments involving kinematic data.
Marianthi-Anna Kioumourtzoglou, ScD, Assistant Professor, Department of Environmental Health Sciences, Columbia University Mailman School of Public Health. Dr. Kioumourtzoglou is an environmental engineer and environmental epidemiologist by training, with a research emphasis on air pollution exposures. Her research focuses on statistical issues related to environmental epidemiology, such as assessing exposure to environmental mixtures (chemical and non-chemical) in health studies, and quantifying and correcting exposure measurement error.
Ander Wilson, PhD, Assistant Professor, Department of Statistics, Colorado State University. Dr. Wilson's research program focuses on developing statistical methods for environmental health research, including estimation of health effects of exposure to environmental mixtures, effect estimate heterogeneity, Bayesian methods, machine learning, and others.
Training scholarships are available for the Environmental Mixtures Workshop.
Summer 2023: The Environmental Mixtures Workshop is an in-person training taking place at the Columbia Mailman School of Public Health located at 722 W. 168th Street in NYC on July 26-27, 2023 from 9am EDT - ~5pm EDT.
More information on travel, lodging, and getting around NYC.
"This workshop provided an excellent overview of modern methods for statistically analyzing mixtures of environmental chemicals. Everyone was really enthusiastic and helpful and I appreciated how easy it was to follow along."- Associate Professor at USF, 2022
"I greatly enjoyed the training. The step-by-step instruction in the labs was incredibly helpful and was useful for understanding how the code is executed and what it is doing. The instructors engaged well with participants and were open to questions." - Research Assistant at Michigan State University, 2022
"The workshop provides a fantastic overview of mixture analysis. It demonstrates method utility using real datasets and provides very helpful materials along the way."- Postdoc at the Florey Institute of Neuroscience and Mental Health, 2022
"Complex mixtures analyses were presented and compared in an easily digestible way. Interactive labs, along with thoughtful discussions with experts and participants, made this workshop a great experience."- Student at Columbia University Medical Center, 2022
"A great two-day introductory workshop on mixtures methods to handle complex exposure data. The instructors are extremely knowledgeable in their subjects and addressed questions really well. The R codes and resources provided are invaluable for my research. I highly recommend this course to anyone who wants to get a quick jumpstart on environmental health data involving complex exposure mixtures."- Postdoc at Columbia University Medical Center, 2022
|Early-Bird Rate (through 5/15/23)||Regular Rate (5/16/23 - 7/19/23)||Columbia Discount*|
|Faculty/Academic Staff/Non-Profit Organizations/Government Agencies||$1,375||$1,575||10%|
*Columbia Discount: This discount is valid for any active student, postdoc, staff, or faculty at Columbia University. If paying by credit card, use your Columbia email address during the registration process to automatically have the discount applied. If paying by internal transfer within Columbia, submit this Columbia Internal Transfer Request form to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.
Invoice Payment: If you would prefer to pay by invoice/check, please submit this Invoice Request form to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.
Registration Fee: Registration Fee includes course material, breakfast, and lunch on training days. Course material will be available to all attendees during and after the workshop. Lodging and transportation are not included.
Cancellations: Cancellation notices must be received via email at least 30 days prior to the training start date in order to receive a full refund, minus a $75 administrative fee. Cancellation notices received via email 14-29 days prior to the training will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to Columbia.Mixtures@gmail.com. Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations <14days prior to the training.
If you are unable to attend the training, we encourage you to send a substitute within the same registration category. Please inform us of the substitute via email at least one week prior to the training to include them on attendee communications, updated registration forms, and materials. Should the substitute fall within a different registration category your credit card will be credited/charged respectively. Please email substitute inquiries to Columbia.Mixtures@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.
- Register for the Environmental Mixtures Workshop.
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- Contact the Boot Camp team.
The Environmental Mixtures Workshop is hosted by Columbia University's SHARP Program with additional support from The Society of Toxicology.
Jump to: Overview | Prerequisites | R tutorials | Instructors | Scholarships | Locations | Testimonials | Registration Fees | Additional Information
"The workshop is very well organized and excellent overview of several major mixtures methods with very helpful examples and materials! I really appreciate all of the instructors!" - Faculty member at Emory University, 2021
"The workshop provided a foundation for using mixture methods in my own research, from identifying appropriate tools for a specific question to implementing analyses. As this field is rapidly changing, it was helpful to learn directly from investigators involved in method development." - Anne B., Postdoc at University of California, Berkeley, 2021
"This is a great introductory workshop to get a good grounding of some mixture methods using real data. The ability to learn about and practice/work through the modeling is particularly helpful." - Postdoc at University of North Carolina at Chapel Hill, 2021
"This workshop will be invaluable for my research. Such a fantastic resource!" - Student at Colorado School of Public Health, 2021
"The workshop gave a good, broad overview of different methods to address different research questions related to environmental mixture analysis. It did a good job of laying the foundation for understanding these methods, even for those with little to no experience with these specific methods before." - Danielle I., Postdoc at Swarthmore College
"Wonderful overview of environmental mixtures methods that will definitely improve my skills as a researcher in my research in both mixtures and non-mixtures research." - Student at University at Albany, 2021
"The workshop was appropriately intense and packed with loads of information and skills to take home for months of practice!" - Faculty member at Emory University, 2020.
"Excellent introduction to tools for analyzing chemical mixtures or other high dimensional data." - Program Officer at NIH, 2020.
"This workshop focused on common methods used in environmental health for understanding mixtures of pollutants. It was a good grounding in the techniques and I learned many things I can use in my current work." - Postdoc at Michigan State University, 2020.
"The workshop presented well-organized and detailed reviews of several mixtures methods using real dataset as an example. Lecturers were all very experienced and materials provided were very useful!" - Student at Emory University, 2020.
"This was an excellent overview of a number of different methods to address mixtures of exposures. The instructors not only explained how the methods work, but also gave interactive examples of which methods might be preferred in specific applications." - Non-profit staff member, 2020.
"I enjoyed hearing from each mixture expert. I feel up-to-date on current mixture methods and enjoyed the 'rapid' overview of many different methods which I can now explore further according to my data and research aims." - Research analyst at NIH, 2020.
"The mixtures workshop was really well done, and I came out of it with an abundance of new knowledge and resources. I really appreciate all of the speakers, as I thought they did a really nice job presenting the material. I can tell how much work was put into this, and I was impressed at how smooth the transitions were from presentation to R lab. I thought it was useful to have a presentation overview and then the hands on lab to view how to conduct the analyses. I thought this was especially well done, considering the necessary quick transition from in-person to virtual. Thanks so much for all your work and for developing this workshop!" - Student at University of California, Berkeley, 2020.
"The Environmental Mixtures workshop is very efficient in covering multiple models for environmental mixtures data. Excellent lectures and hands-on practices!" - Postdoc at Columbia University, 2020.
"This workshop is a really nice overview of the major mixtures methods currently being used in environmental health. Even as an individual with no prior mixtures methods experience, I was able to gain a solid foundation in these mixtures methods to apply to my own research." - Student at Michigan State University, 2020.
"Great workshop and would recommend to anyone in the field of environmental health." - Faculty member at Maine Medical Center, 2020.
"A fantastic primer to enter the field of mixtures research- helpful briefings on the theory but a great emphasis on practical application including useful example code." - Student at the University of North Carolina, Chapel Hill, 2020.
"Excellent workshop taught by experts in cutting-edge methods for parsing and analyzing the combined effects of mixtures of environmental pollutants on health outcomes. The methods are extensible for other applications, such as reducing the dimensionality of outcome data and/or for investigating other non-environmental exposures. All materials and code are provided." - Health scientist attendee, 2019.
"The quality of the teaching is incredible -- the lectures are worth it even if you have no intention of using these methods. The instructors are that good. The matched lecture-lab sequence is a great way to introduce and apply these topics, and makes them relevant to a broad audience. And, thank you for using a standard data set and lab example across all methods. That makes so much sense." - Postdoc at NIEHS, 2019.
"Excellent workshop! I am just learning R, and did not feel debilitated at all. I greatly appreciated the html code where I could follow along and takes notes. Wonderful experience. Thank you!" - Postdoc at the University of Toronto, 2019.
"Amazing workshop with instructors that were very knowledgeable and open about the techniques uses and limitations. Support staff was really helpful, and I learned a lot from this short training - thank you!" - PhD student from Oregon State University, 2019.
"Fantastic opportunity to learn state of the art mixtures methodologies." - Postdoc at Dartmouth College, 2018.
"Great job! I learned a lot about the methods I will be using in my research. It was a perfect mix of theory and practical applications (R code)." - Postdoc at Icahn School of Medicine at Mount Sinai, 2018.
"Interesting, informing and interactive." - Student at Northeastern University, 2018.
"It's a great primer/workshop that is accessible to all epidemiologist/statisticians working on related fields. I think it's supremely helpful for anyone trying to get started on this." - Postdoc at Columbia University, 2018.
"This was an excellent distillation of incredibly challenging concepts. The resources provided were fantastic." - Student attendee, 2018.
"Excellent overview of range of different methods to use when studying environmental mixtures. It was very helpful to use the R code during lab sections and get a taste of what running the code will be like." - Postdoc at University of California, San Francisco, 2018.