Short Courses on Obesity, Mathematics, and Causal Inference in Summer 2022!
We invite you to join us at one or both of our remote, NIH-funded short courses being hosted this summer.
The Mathematical Sciences in Obesity Research
Dates: June 17th – July 8th, 2022 (Virtual Event)
Format: Remote, synchronous sessions on Friday afternoons (tentatively from noon to 2 pm Eastern), with asynchronous material through IU Expand.
Course description: The mathematical sciences including engineering, statistics, computer science, physics, econometrics, psychometrics, epidemiology, and mathematics qua mathematics are increasingly being applied to advance our understanding of the causes, consequences, and alleviation of obesity. These applications do not merely involve routine, well-established approaches easily implemented in widely available commercial software. Rather, they increasingly involve computationally demanding tasks, use and development of novel analytic methods and software, new derivations, computer simulations, and unprecedented interdigitation of two or more existing techniques. Such advances at the interface of the mathematical sciences and obesity research require bilateral training and exposure for investigators in both disciplines.
To apply: Visit our course site at The Mathematical Sciences in Obesity
Strengthening Causal Inference in Behavioral Obesity Research
Dates: July 29th – August 19th, 2022 (Virtual Event)
Format: Remote, synchronous sessions on Friday afternoons (tentatively 12 pm to 2 pm Eastern), with asynchronous material during the weeks.
Course description: Identifying causal relations among variables is fundamental to science. Obesity is a major problem for which much progress in understanding, treatment, and prevention remains to be made. Understanding which social and behavioral factors cause variations in adiposity is vital to producing, evaluating, and selecting intervention and prevention strategies. In addition, developing a greater understanding of obesity’s causes requires input from diverse disciplines including statistics, economics, psychology, epidemiology, mathematics, philosophy, and behavioral or statistical genetics. However, applying techniques from these disciplines does not involve routine well-known ‘cookbook’ approaches. Rather, an understanding of the underlying principles is required so that the investigator can tailor approaches to specific and varying situations.
To apply: Visit our course site at Strengthening Causal Inference in Behavioral Obesity Research
Spaces are limited to encourage more engagement among participants and with course faculty, so apply soon. Persons of all genders, race/ethnicities, and ability/disability statuses are strongly encouraged to apply.
We look forward to seeing you this summer!
David Allison, Ph.D., Indiana University
Andrew Brown, Ph.D., Indiana University
Diana Thomas, Ph.D., USMA West Point
Kevin Fontaine, Ph.D., University of Alabama at Birmingham