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Identification theory for causal effects in causal models associated with hidden variable directed acyclic graphs (DAGs) is well studied.
A primal-dual algorithm
George B. Dantzig, Lester R. Ford Jr., and Delbert R. Fulkerson · 1956
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A characterization of limiting distributions of regular estimates
Jaroslav Hájek · 1970
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Depth-first search and linear graph algorithms
Robert Tarjan · 1972
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The influence curve and its role in robust estimation
Frank R. Hampel · 1974
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A new approach to causal inference in mortality studies with a sustained exposure period – application to control of the healthy worker survivor effect
James M. Robins · 1986
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Semiparametric efficiency bounds
Whitney K. Newey · 1990
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Equivalence and synthesis of causal models
Thomas Verma and Judea Pearl · 1990
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Estimating exposure effects by modelling the expectation of exposure conditional on confounders
James M Robins, Steven D Mark, and Whitney K Newey · 1992
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Efficient and adaptive estimation for semiparametric models , volume 4
Peter J. Bickel, Chris A.J. Klaassen, Ya’acov Ritov, and Jon A. Wellner · 1993
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Estimation of regression coefficients when some regressors are not always observed
James M. Robins, Andrea Rotnitzky, and Lue Ping Zhao · 1994
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Causal diagrams for empirical research
Judea Pearl · 1995
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Graphical Models
Steffen L. Lauritzen · 1996
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Optimization by Vector Space Methods
David G. Luenberger · 1997
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On the role of the propensity score in efficient semiparametric estimation of average treatment effects
Jinyong Hahn · 1998
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Causal diagrams for epidemiologic research
Sander Greenland, Judea Pearl, and James M. Robins · 1999
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Marginal structural models versus structural nested models as tools for causal inference
James M. Robins · 2000
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Causation, prediction, and search
Peter L. Spirtes, Clark N. Glymour, Richard Scheines, David Heckerman, Christopher Meek, Gregory Cooper, and Thomas S. Richardson · 2000
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Asymptotic Statistics , volume 3
Aad W. van der Vaart · 2000
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Semiparametric instrumental variable estimation of treatment response models
Alberto Abadie · 2003
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Markov properties for acyclic directed mixed graphs
Thomas S. Richardson · 2003
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Unified methods for censored longitudinal data and causality
Mark J. van der Laan and James M. Robins · 2003
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Convex Optimization
Stephen P. Boyd and Lieven Vandenberghe · 2004
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Doubly robust estimation in missing data and causal inference models
Heejung Bang and James M. Robins · 2005
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Pearl’s calculus of intervention is complete
Yimin Huang and Marco Valtorta · 2006
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Identification of joint interventional distributions in recursive semi-Markovian causal models
Ilya Shpitser and Judea Pearl · 2006
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Nested Markov properties for acyclic directed mixed graphs
Thomas S. Richardson, Robin J. Evans, James M. Robins, and Ilya Shpitser · 2017
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Simplifying probabilistic expressions in causal inference
Santtu Tikka and Juha Karvanen · 2017
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Double/debiased machine learning for treatment and structural parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney K. Newey, and James M. Robins · 2018
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Margins of discrete Bayesian networks
Robin J. Evans · 2018
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Acyclic linear SEMs obey the nested Markov property
Ilya Shpitser, Robin J. Evans, and Thomas S. Richardson · 2018
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Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables
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Semiparametric theory and missing data
Anastasios Tsiatis · 2007
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Higher order influence functions and minimax estimation of nonlinear functionals
J. Robins, L. Li, E. Tchetgen, and A. van der Vaart · 2008
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Discrete chain graph models
Mathias Drton · 2009
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Causality
Judea Pearl · 2009
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On the validity of covariate adjustment for estimating causal effects
Ilya Shpitser, Tyler J. VanderWeele, and James M. Robins · 2010
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Dimensionality reduction for density ratio estimation in high-dimensional spaces
Masashi Sugiyama, Motoaki Kawanabe, and Pui Ling Chui · 2010
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Linbo Wang and Eric J. Tchetgen Tchetgen · 2018
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Directed acyclic graphs: a tool for causal studies in paediatrics
Thomas C. Williams, Cathrine C. Bach, Niels B. Matthiesen, Tine B. Henriksen, and Luigi Gagliardi · 2018
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Toward computerized efficient estimation in infinite-dimensional models
Marco Carone, Alexander R. Luedtke, and Mark J. van der Laan · 2019
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Smooth, identifiable supermodels of discrete DAG models with latent variables
Robin J. Evans and Thomas S. Richardson · 2019
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Causal inference and data-fusion in econometrics
Paul Hünermund and Elias Bareinboim · 2019
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A potential outcomes calculus for identifying conditional path-specific effects
Daniel Malinsky, Ilya Shpitser, and Thomas S. Richardson · 2019
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Robust inference on population indirect causal effects: the generalized front door criterion
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