Associate professor of health care policy Sherri Rose, PhD, has published Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies with Mark J. van der Laan.

This textbook, intended for use by graduate students and scholars in statistics, data science, and public health, deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications, including those found in health care policy, into formal statistical estimation problems by using the general template of (targeted) maximum likelihood estimators. It investigates machine learning methods for causal inference within data science and explains how to utilize them to answer complex questions in dependent data structures.

Targeted Learning in Data Science includes demonstrations with software packages and real data sets. This book is the sequel to Targeted Learning, which was published by van der Laan and Rose in 2011.

This textbook is printed by Springer Publishing in 2018.