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book.bib
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@book{davison1997bootstrap,
title={Bootstrap Methods and Their Application},
author={Davison, Anthony Christopher and Hinkley, David Victor},
year={1997},
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@article{holland1986statistics,
title={Statistics and causal inference},
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journal={Journal of the American Statistical Association},
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}
@book{fisher1946statistical,
title={Statistical Methods for Research Workers},
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@book{hernan2022causal,
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publisher = {CRC Press},
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year = {2022}
}
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@article{diaz2012population,
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@book{vdl2018targeted,
title={Targeted Learning in Data Science: Causal Inference for Complex
Longitudinal Studies},
author={{van der Laan}, Mark J and Rose, Sherri},
year={2018},
publisher={Springer Science \& Business Media}
}
@book{vdl2011targeted,
title={Targeted learning: causal inference for observational and experimental
data},
author={{van der Laan}, Mark J and Rose, Sherri},
year={2011},
publisher={Springer Science \& Business Media}
}
@article{diaz2011super,
title={Super learner based conditional density estimation with application to
marginal structural models},
author={D{\'\i}az, Iv{\'a}n and {van der Laan}, Mark J},
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volume={7},
number={1},
pages={1--20},
year={2011},
publisher={De Gruyter}
}
@incollection{diaz2018stochastic,
title={Stochastic Treatment Regimes},
author={D{\'\i}az, Iv{\'a}n and {van der Laan}, Mark J},
booktitle={Targeted Learning in Data Science: Causal Inference for Complex
Longitudinal Studies},
pages={167--180},
year={2018},
publisher={Springer Science \& Business Media}
}
@article{vdl2006targeted,
title={Targeted maximum likelihood learning},
author={{van der Laan}, Mark J and Rubin, Daniel},
journal={The International Journal of Biostatistics},
volume={2},
number={1},
year={2006}
}
@article{vdl2004asymptotic,
title={Asymptotic optimality of likelihood-based cross-validation},
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volume={3},
number={1},
pages={1--23},
year={2004}
}
@article{dudoit2005asymptotics,
title={Asymptotics of cross-validated risk estimation in estimator selection
and performance assessment},
author={Dudoit, Sandrine and {van der Laan}, Mark J},
journal={Statistical Methodology},
volume={2},
number={2},
pages={131--154},
year={2005},
publisher={Elsevier}
}
@article{vdl2007super,
title={{Super Learner}},
author={{van der Laan}, Mark J and Polley, Eric C and Hubbard, Alan E},
journal={Statistical Applications in Genetics and Molecular Biology},
volume={6},
number={1},
year={2007}
}
@book{pearl2009causality,
title={Causality: Models, Reasoning, and Inference},
author={Pearl, Judea},
year={2009},
publisher={Cambridge University Press}
}
@article{holland1986statistics,
title={Statistics and causal inference},
author={Holland, Paul W},
journal={Journal of the American statistical Association},
volume={81},
number={396},
pages={945--960},
year={1986},
publisher={Taylor \& Francis}
}
@article{rosenbaum1983central,
title={The central role of the propensity score in observational studies for
causal effects},
author={Rosenbaum, Paul R and Rubin, Donald B},
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volume={70},
number={1},
pages={41--55},
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publisher={Biometrika Trust}
}
@article{haneuse2013estimation,
title={Estimation of the effect of interventions that modify the received
treatment},
author={Haneuse, Sebastian and Rotnitzky, Andrea},
journal={Statistics in medicine},
volume={32},
number={30},
pages={5260--5277},
year={2013},
publisher={Wiley Online Library}
}
@article{young2014identification,
title={Identification, estimation and approximation of risk under
interventions that depend on the natural value of treatment using
observational data},
author={Young, Jessica G and Hern{\'a}n, Miguel A and Robins, James M},
journal={Epidemiologic methods},
volume={3},
number={1},
pages={1--19},
year={2014},
publisher={De Gruyter}
}
@article{rubin1978bayesian,
title={Bayesian inference for causal effects: The role of randomization},
author={Rubin, Donald B},
journal={The Annals of statistics},
pages={34--58},
year={1978},
publisher={JSTOR}
}
@article{rubin1980randomization,
title={Randomization analysis of experimental data: The Fisher randomization
test comment},
author={Rubin, Donald B},
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volume={75},
number={371},
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year={1980},
publisher={JSTOR}
}
@article{kennedy2019nonparametric,
title={Nonparametric causal effects based on incremental propensity score
interventions},
author={Kennedy, Edward H},
journal={Journal of the American Statistical Association},
volume={114},
number={526},
pages={645--656},
year={2019},
publisher={Taylor \& Francis}
}
@article{cvtmle2010,
author = {Zheng, Wenjing and {van der Laan}, Mark J},
title = "{Asymptotic Theory for Cross-validated Targeted Maximum Likelihood
Estimation}",
journal = {U.C.~Berkeley Division of Biostatistics Working Paper Series},
year = 2010,
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}
@article{luedtke2016super,
Author = {Luedtke, Alex and {van der Laan}, Mark J},
Journal = {International Journal of Biostatistics},
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Title = {Super-learning of an optimal dynamic treatment rule},
Volume = {12},
Year = {2016}
}
@article{vanderLaanLuedtke15,
Author = {{van der Laan}, Mark J and Luedtke, Alex},
Journal = {Journal of Causal Inference},
Note = {PMCID: PMC4517487},
Number = {1},
Pages = {61--95},
Title = {Targeted learning of the mean outcome under an optimal dynamic
treatment rule},
Volume = {3},
Year = {2015}
}
@book{Sutton1998,
title={Introduction to reinforcement learning},
author={Sutton, Richard S and Barto, Andrew G and others},
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}
@article{murphy2003,
title={Optimal dynamic treatment regimes},
author={Murphy, Susan A},
journal={Journal of the Royal Statistical Society: Series B (Statistical
Methodology)},
volume={65},
number={2},
pages={331--355},
year={2003},
publisher={Wiley Online Library}
}
@inproceedings{robins2004,
author={Robins, James M},
title={Optimal Structural Nested Models for Optimal Sequential Decisions},
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Analysis of Correlated Data},
year={2004},
publisher={Springer New York},
pages={189--326},
doi={10.1007/978-1-4419-9076-1_11},
url={https://doi.org/10.1007/978-1-4419-9076-1_11}
}
@article{vdl2014entering,
title={Entering the era of data science: Targeted learning and the
integration of statistics and computational data analysis},
author={{van der Laan}, Mark J and Starmans, Richard JCM},
journal={Advances in Statistics},
volume={2014},
year={2014},
publisher={Hindawi}
}
@techreport{vdl2003unified,
title={Unified cross-validation methodology for selection among estimators
and a general cross-validated adaptive epsilon-net estimator: Finite sample
oracle inequalities and examples},
author={{van der Laan}, Mark J and Dudoit, Sandrine},
year={2003},
publisher={bepress},
institution={{Division of Biostatistics, University of California, Berkeley}}
}
@article{wolpert1992stacked,
title={Stacked generalization},
author={Wolpert, David H},
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}
@article{naturenews_2015,
author = {{\textit{Nature} Editorial (Anonymous)}},
title={Let’s think about cognitive bias},
journal={Nature},
publisher={Springer Nature},
year={2015},
month={Oct},
volume={526},
number={7572},
doi={10.1038/526163a}
}
@article{peng2015reproducibility,
title={The reproducibility crisis in science: A statistical counterattack},
author={Peng, Roger},
journal={Significance},
volume={12},
number={3},
pages={30--32},
year={2015},
publisher={Wiley Online Library}
}
@article{munafo2017manifesto,
title={A manifesto for reproducible science},
author={Munaf{\`o}, Marcus R and Nosek, Brian A and Bishop, Dorothy VM and
Button, Katherine S and Chambers, Christopher D and Du Sert, Nathalie
Percie and Simonsohn, Uri and Wagenmakers, Eric-Jan and Ware, Jennifer J
and Ioannidis, John PA},
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volume={1},
number={1},
pages={0021},
year={2017},
publisher={Nature Publishing Group}
}
@article{naturenews2_2015,
author = {{\textit{Nature} Editorial (Anonymous)}},
title={How scientists fool themselves --- and how they can stop},
journal={Nature},
publisher={Springer Nature},
year={2015},
month={Oct},
volume={526},
number={7572}
}
@article{forstmeier2017detecting,
title={Detecting and avoiding likely false-positive findings--a practical
guide},
author={Forstmeier, Wolfgang and Wagenmakers, Eric-Jan and Parker, Timothy
H},
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volume={92},
number={4},
pages={1941--1968},
year={2017},
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}
@article{nosek2018preregistration,
title={The preregistration revolution},
author={Nosek, Brian A and Ebersole, Charles R and DeHaven, Alexander C and
Mellor, David T},
journal={Proceedings of the National Academy of Sciences},
volume={115},
number={11},
pages={2600--2606},
year={2018},
publisher={National Academy of Sciences}
}
@article{baker2016there,
title={Is there a reproducibility crisis? A Nature survey lifts the lid on
how researchers view the crisis rocking science and what they think will
help},
author={Baker, Monya},
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volume={533},
number={7604},
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year={2016},
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}
@article{szucs2017null,
title={When null hypothesis significance testing is unsuitable for research:
a reassessment},
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}
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title={Knowledge translation in biostatistics: a survey of current practices,
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}
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title={Why write statistical software? The case of robust statistical
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title={Wavelab and reproducible research},
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@book{kitzes2017practice,
title={The practice of reproducible research: case studies and lessons from
the data-intensive sciences},
author={Kitzes, Justin and Turek, Daniel and Deniz, Fatma},
year={2017},
publisher={Univ of California Press}
}
@article{luby2018effect,
title={Effect of water quality, sanitation, hand washing, and nutritional
interventions on child development in rural Bangladesh (WASH Benefits
Bangladesh): a cluster-randomised controlled trial},
author={Tofail, Fahmida and Fernald, Lia CH and Das, Kishor K and Rahman,
Mahbubur and Ahmed, Tahmeed and Jannat, Kaniz K and Unicomb, Leanne and
Arnold, Benjamin F and Ashraf, Sania and Winch, Peter J and others},
journal={The Lancet Child \& Adolescent Health},
volume={2},
number={4},
pages={255--268},
year={2018},
publisher={Elsevier}
}
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title={On the application of probability to agricultural experiments. Essay
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}
@article{robins1986,
title = "A new approach to causal inference in mortality studies with a
sustained exposure period—application to control of the healthy worker
survivor effect",
journal = "Mathematical Modelling",
volume = "7",
number = "9",
pages = "1393 - 1512",
year = "1986",
issn = "0270-0255",
doi = "https://doi.org/10.1016/0270-0255(86)90088-6",
author = "James Robins"
}
@book{pearl2009,
author = {Pearl, Judea},
title = {Causality: Models, Reasoning and Inference},
year = {2009},
isbn = {052189560X, 9780521895606},
edition = {2nd},
publisher = {Cambridge University Press},
address = {New York, NY, USA},
}
@book{moodie2013,
Author = {Chakraborty, Bibhas and Moodie, Erica EM},
Title = {Statistical Methods for Dynamic Treatment Regimes: Reinforcement
Learning, Causal Inference, and Personalized Medicine (Statistics for
Biology and Health)},
Publisher = {Springer},
Year = {2013},
ISBN = {1461474272},
}
@article{laber2012,
author = {Zhang, Baqun and A Tsiatis, Anastasios and Davidian, Marie and
Zhang, Min and Laber, Eric},
title = {Estimating optimal treatment regimes from a classification
perspective},
journal = {Stat},
volume = {5},
number = {1},
pages = {278-278},
doi = {10.1002/sta4.124},
year = {2016}
}
@article{kosorok2012,
author = {Yingqi Zhao and Donglin Zeng and A John Rush and Michael R
Kosorok},
title = {Estimating Individualized Treatment Rules Using Outcome Weighted
Learning},
journal = {Journal of the American Statistical Association},
volume = {107},
number = {499},
pages = {1106-1118},
year = {2012},
publisher = {Taylor \& Francis},
doi = {10.1080/01621459.2012.695674},
note ={PMID: 23630406}
}
@article{robins2014,
author = "Robins, James and Rotnitzky, Andrea",
doi = "10.1214/14-EJS908",
fjournal = "Electronic Journal of Statistics",
journal = "Electron. J. Statist.",
number = "1",
pages = "1273--1289",
publisher = "The Institute of Mathematical Statistics and the Bernoulli
Society",
title = "Discussion of “Dynamic treatment regimes: Technical challenges and
applications”",
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