A paper by former health care policy Seidman fellow Megan S. Schuler PhD, and associate professor of health care policy Sherri Rose, PhD, titled “Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies” has been selected as one of the American Journal of Epidemiology and Society for Epidemiologic Research’s 2017 Articles of the Year.

The American Journal of Epidemiology selects ten papers each year that are leading the field of epidemiology, epidemiologic methods, and are at the cutting edge of epidemiologic science. Schuler and Rose’s study discusses the use of targeted maximum likelihood estimation (TMLE) methods as an alternative to propensity score methods or G-computation when estimating a causal effect.

Schuler and Rose are recognized in the April 2018 issue of the Journal, and will be formally recognized at the Society for Epidemiologic Research’s Annual Meeting in Baltimore, Maryland in June 2018.