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Targeted Learning in Data Science

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Cover of 'Targeted Learning in Data Science'

Table of Contents

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    Book Overview
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    Chapter 1 Research Questions in Data Science
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    Chapter 2 Defining the Model and Parameter
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    Chapter 3 Sequential Super Learning
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    Chapter 4 LTMLE
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    Chapter 5 One-Step TMLE
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    Chapter 6 Highly Adaptive Lasso (HAL)
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    Chapter 7 A Generally Efficient HAL-TMLE
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    Chapter 8 HAL Estimator of the Efficient Influence Curve
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    Chapter 9 Data-Adaptive Target Parameters
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    Chapter 10 C-TMLE for Continuous Tuning
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    Chapter 11 Targeted Estimation of Cumulative Vaccine Sieve Effects
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    Chapter 12 The Sample Average Treatment Effect
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    Chapter 13 Data-Adaptive Estimation in Cluster Randomized Trials
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    Chapter 14 Stochastic Treatment Regimes
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    Chapter 15 LTMLE with Clustering
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    Chapter 16 Comparative Effectiveness of Adaptive Treatment Strategies
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    Chapter 17 Mediation Analysis with Time-Varying Mediators and Exposures
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    Chapter 18 Online Super Learning
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    Chapter 19 Online Targeted Learning for Time Series
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    Chapter 20 Causal Inference in Longitudinal Network-Dependent Data
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    Chapter 21 Single Time Point Interventions in Network-Dependent Data
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    Chapter 22 Optimal Dynamic Treatment Rules
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    Chapter 23 Optimal Individualized Treatments Under Limited Resources
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    Chapter 24 Targeting a Simple Statistical Bandit Problem
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    Chapter 25 CV-TMLE for Nonpathwise Differentiable Target Parameters
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    Chapter 26 Higher-Order Targeted Loss-Based Estimation
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    Chapter 27 Sensitivity Analysis
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    Chapter 28 Targeted Bootstrap
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    Chapter 29 Targeted Learning Using Adaptive Survey Sampling
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    Chapter 30 The Predicament of Truth: On Statistics, Causality, Physics, and the Philosophy of Science
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