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Item Details
| Title:
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TARGETED LEARNING IN DATA SCIENCE
CAUSAL INFERENCE FOR COMPLEX LONGITUDINAL STUDIES |
| By: |
Mark J. van der Laan, Sherri Rose |
| Format: |
Hardback |
| List price:
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£109.99 |
| Our price: |
£93.49 |
| Discount: |
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| You save:
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£16.50 |
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| ISBN 10: |
3319653032 |
| ISBN 13: |
9783319653037 |
| Availability: |
Usually dispatched within 3-5 days.
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rates
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| Stock: |
Currently 2 available |
| Publisher: |
SPRINGER INTERNATIONAL PUBLISHING AG |
| Pub. date: |
25 October, 2017 |
| Edition: |
1st ed. 2017 |
| Series: |
Springer Series in Statistics |
| Pages: |
632 |
| Synopsis: |
This textbook for Masters and PhD graduate students in biostatistics, statistics, data science, and epidemiology deals with the practical challenges that come with big, complex, and dynamic data while maintaining a strong theoretical foundation. 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 to construct targeted machine learning algorithms that incorporate the state-of-the-art in machine learning to estimate quantities of interest, while still providing valid inference. Targeted learning methods within data science are a critical component for answering complex statistical questions in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data involving time-dependent confounding and censoring as well as other estimands in dependent data structures, such as networks. Standard methods and software tools are not currently equipped for these challenges; however, targeted learning is tailored for these problems found in precision medicine, big data, and data science. Included in Targeted Learning in Data Science are demonstrations with software packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. |
| Illustrations: |
33 Illustrations, black and white; X, 632 p. 33 illus. |
| Publication: |
Switzerland |
| Imprint: |
Springer International Publishing AG |
| Returns: |
Returnable |
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