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 Gender and Political Marketing in the United States and the 2016 Presidential Election by Sherri Rose, Mark J. van der Laan
Cover of the book Constraint Theory by Sherri Rose, Mark J. van der Laan
Cover of the book Risk Assessment by Sherri Rose, Mark J. van der Laan
Cover of the book Non-minimal Higgs Inflation and Frame Dependence in Cosmology by Sherri Rose, Mark J. van der Laan
Cover of the book Set Theory by Sherri Rose, Mark J. van der Laan
Cover of the book Software Developers as Users by Sherri Rose, Mark J. van der Laan
Cover of the book Computing and Combinatorics by Sherri Rose, Mark J. van der Laan
Cover of the book Computational Methods for Application in Industry 4.0 by Sherri Rose, Mark J. van der Laan
Cover of the book The Hermeneutics of Hell by Sherri Rose, Mark J. van der Laan
Cover of the book Recent Advances in Computational Optimization by Sherri Rose, Mark J. van der Laan
Cover of the book Case-Based Reasoning Research and Development by Sherri Rose, Mark J. van der Laan
Cover of the book Uncertainty Modeling by Sherri Rose, Mark J. van der Laan
Cover of the book Finite Element Applications by Sherri Rose, Mark J. van der Laan
Cover of the book Governing Business Systems by Sherri Rose, Mark J. van der Laan
Cover of the book Exploring Animal Encounters 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