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Targeted Learning: Causal Inference for Observational and Experimental Data

1. Aufl., 2011

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Parametric-Rate Inference for One-Sided Differentiable Parameters

Journal of the American Statistical Association, 2018-04, Vol.113 (522), p.780-788

2018

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Personalized online ensemble machine learning with applications for dynamic data streams

Statistics in medicine, 2023-03, Vol.42 (7), p.1013-1044

2023

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Population intervention models in causal inference

Biometrika, 2008-03, Vol.95 (1), p.35-47

2008

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Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels

PLoS neglected tropical diseases, 2017-05, Vol.11 (5), p.e0005616

2017

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STATISTICAL INFERENCE FOR THE MEAN OUTCOME UNDER A POSSIBLY NON-UNIQUE OPTIMAL TREATMENT STRATEGY

The Annals of statistics, 2016-04, Vol.44 (2), p.713-742

2016

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Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation

The International Journal of Biostatistics, 2009-01, Vol.5 (1), p.1-Article 1

2009

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Causal Inference for Social Network Data

Journal of the American Statistical Association, 2024, Vol.119 (545), p.597-611

2024

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One‐step targeted maximum likelihood estimation for time‐to‐event outcomes

Biometrics, 2020-09, Vol.76 (3), p.722-733

2020

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Data-Adaptive Selection of the Propensity Score Truncation Level for Inverse-Probability–Weighted and Targeted Maximum Likelihood Estimators of Marginal Point Treatment Effects

American journal of epidemiology, 2022-08, Vol.191 (9), p.1640-1651

2022

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Estimation of time‐specific intervention effects on continuously distributed time‐to‐event outcomes by targeted maximum likelihood estimation

Biometrics, 2023-12, Vol.79 (4), p.3038-3049

2023

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Diagnosing and responding to violations in the positivity assumption

Statistical methods in medical research, 2012-02, Vol.21 (1), p.31-54

2012

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tmle : An R Package for Targeted Maximum Likelihood Estimation

Journal of statistical software, 2012-11, Vol.51 (13)

2012

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Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso

Biometrics, 2023-06, Vol.79 (2), p.1029-1041

2023

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Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study

The lancet respiratory medicine, 2015, Vol.3 (1), p.42-52

2015

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Efficient targeted learning of heterogeneous treatment effects for multiple subgroups

Biometrics, 2023-09, Vol.79 (3), p.1934-1946

2023

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Improved Small-Sample Estimation of Nonlinear Cross-Validated Prediction Metrics

Journal of the American Statistical Association, 2020, Vol.115 (532), p.1917-1932

2020

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Selecting Optimal Subgroups for Treatment Using Many Covariates

Epidemiology (Cambridge, Mass.), 2019-05, Vol.30 (3), p.334-341

2019

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Defining and estimating effects in cluster randomized trials: A methods comparison

Statistics in medicine, 2023-08, Vol.42 (19), p.3443-3466

2023

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An omnibus non-parametric test of equality in distribution for unknown functions

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2019-02, Vol.81 (1), p.75-99

2019

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Robust inference on the average treatment effect using the outcome highly adaptive lasso

Biometrics, 2020-03, Vol.76 (1), p.109-118

2020

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Rachael V. Phillips and Mark J. van der Laan’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2022-07, Vol.84 (3), p.717-718

2022

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Targeted learning with daily EHR data

Statistics in medicine, 2019-07, Vol.38 (16), p.3073-3090

2019

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Estimation of the Optimal Surrogate Based on a Randomized Trial

Biometrics, 2018-12, Vol.74 (4), p.1271-1281

2018

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Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard

Biometrics, 2023-03, Vol.79 (1), p.20-22

2023

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Targeted Learning: Causal Inference for Observational and Experimental Data

Parametric-Rate Inference for One-Sided Differentiable Parameters

Personalized online ensemble machine learning with applications for dynamic data streams

Population intervention models in causal inference

Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels

STATISTICAL INFERENCE FOR THE MEAN OUTCOME UNDER A POSSIBLY NON-UNIQUE OPTIMAL TREATMENT STRATEGY

Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation

Causal Inference for Social Network Data

One‐step targeted maximum likelihood estimation for time‐to‐event outcomes

Data-Adaptive Selection of the Propensity Score Truncation Level for Inverse-Probability–Weighted and Targeted Maximum Likelihood Estimators of Marginal Point Treatment Effects

Estimation of time‐specific intervention effects on continuously distributed time‐to‐event outcomes by targeted maximum likelihood estimation

Diagnosing and responding to violations in the positivity assumption

tmle : An R Package for Targeted Maximum Likelihood Estimation

Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso

Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study

Efficient targeted learning of heterogeneous treatment effects for multiple subgroups

Improved Small-Sample Estimation of Nonlinear Cross-Validated Prediction Metrics

Selecting Optimal Subgroups for Treatment Using Many Covariates

Defining and estimating effects in cluster randomized trials: A methods comparison

An omnibus non-parametric test of equality in distribution for unknown functions

Robust inference on the average treatment effect using the outcome highly adaptive lasso

Rachael V. Phillips and Mark J. van der Laan’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes

Targeted learning with daily EHR data

Estimation of the Optimal Surrogate Based on a Randomized Trial

Discussion on “Adaptive enrichment designs with a continuous biomarker” by Nigel Stallard

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