Thomas Stopka is an associate professor and epidemiologist with the Department of Public Health and Community Medicine at the Tufts University School of Medicine. In his NIH-funded interdisciplinary ...

The analysis of longitudinal dyadic data is challenging due to the complicated correlations within and between dyads, as well as possibly non-ignorable dropouts. Based on a mixed-effects hybrid model, ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

The network autocorrelation model has been the workhorse for estimating and testing the strength of theories of social influence in a network. In many network studies, different types of social ...

2024 - Bristol-Meyers Squibb was awarded for “PMI Prediction and Bayesian Optimization: Two Tools with One Goal Towards the Development of ‘Greener-by-Design’ Synthesis of APIs” Read more about BMS’s ...