Targeted Learning in Data Science

Causal Inference for Complex Longitudinal Studies

Nonfiction, Science & Nature, Mathematics, Statistics, Business & Finance, Industries & Professions, Industries
Cover of the book Targeted Learning in Data Science by Sherri Rose, Mark J. van der Laan, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Sherri Rose, Mark J. van der Laan ISBN: 9783319653044
Publisher: Springer International Publishing Publication: March 28, 2018
Imprint: Springer Language: English
Author: Sherri Rose, Mark J. van der Laan
ISBN: 9783319653044
Publisher: Springer International Publishing
Publication: March 28, 2018
Imprint: Springer
Language: English

This textbook for graduate students 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 into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011.

Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics.

Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This textbook for graduate students 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 into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011.

Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics.

Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.

More books from Springer International Publishing

Cover of the book Event-Based State Estimation by Sherri Rose, Mark J. van der Laan
Cover of the book Fear of Muslims? by Sherri Rose, Mark J. van der Laan
Cover of the book Hayek: A Collaborative Biography by Sherri Rose, Mark J. van der Laan
Cover of the book Psychiatry and Neuroscience Update - Vol. II by Sherri Rose, Mark J. van der Laan
Cover of the book Shaping American Democracy by Sherri Rose, Mark J. van der Laan
Cover of the book Robotic Grasping and Manipulation by Sherri Rose, Mark J. van der Laan
Cover of the book Therapy in Pediatric Dermatology by Sherri Rose, Mark J. van der Laan
Cover of the book Cyber Racism and Community Resilience by Sherri Rose, Mark J. van der Laan
Cover of the book Sexuality, Iconography, and Fiction in French by Sherri Rose, Mark J. van der Laan
Cover of the book Internet of Things. IoT Infrastructures by Sherri Rose, Mark J. van der Laan
Cover of the book The Invention of Time and Space by Sherri Rose, Mark J. van der Laan
Cover of the book Software Engineering Education for a Global E-Service Economy by Sherri Rose, Mark J. van der Laan
Cover of the book Deep Experiencing by Sherri Rose, Mark J. van der Laan
Cover of the book Artificial Intelligence and Economic Theory: Skynet in the Market by Sherri Rose, Mark J. van der Laan
Cover of the book Climate Technology, Gender, and Justice by Sherri Rose, Mark J. van der Laan
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy