Targeted Learning

Name: Targeted Learning
Brand: Springer-Verlag New York Inc.
SKU: 9781441997814
Price: 724.91 PLN
Availability: InStock

Causal Inference for Observational and Experimental Data

Autor: Mark Van der Laan, Sherri Rose

Język:

Oprawa: Twarda

Wydawca: Springer-Verlag New York Inc.

Dostępność: Dostępna u dostawcy

Wysyłamy za 10-18 dni

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The statistics profession is at a unique point in history. The need for valid statistical tools is g...

Informacje o książce

Autor

Mark Van der Laan, Sherri Rose

Język

Angielski

Oprawa

Książka - Twarda

Data wydania

2011

strony

628

EAN

9781441997814

ISBN

1441997814

Enbook ID

01424609

Wydawca

Springer-Verlag New York Inc.

Waga

1208

Wymiary

241 x 167 x 43

Pełny opis

The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. §This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including continuous outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.

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Targeted Learning

Causal Inference for Observational and Experimental Data

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