Tyler McCormick

McCormick's work develops statistical models for inference and prediction in scientific settings where data are sparsely observed or measured with error. His recent projects include estimating features of social networks (e.g. the degree of clustering or how central an individual is) using data from standard surveys, inferring a likely cause of death (when deaths happen outside of hospitals) using reports from surviving caretakers, and quantifying & communicating uncertainty in predictive models for global health policymakers.