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Adjusting for covariates is a well established method to estimate the total causal effect of an exposure variable on an outcome of interest.
The large-sample distribution of the likelihood ratio for testing composite hypotheses
S. S. Wilks · 1938
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[Bayesian analysis in expert systems]: Comment: graphical models, causality and intervention
J. Pearl · 1993
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Causal diagrams for empirical research
J. Pearl · 1995
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Causal diagrams for epidemiologic research
S. Greenland, J. Pearl, and J. M. Robins · 1999
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Causality: models, reasoning and inference
J. Pearl · 2000
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Causation, prediction, and search
P. Spirtes, C. N. Glymour, and R. Scheines · 2000
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Optimal structure identification with greedy search
D. M. Chickering · 2002
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Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks
N. Friedman and D. Koller · 2003
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generatingfunctionology
H. S. Wilf · 2005
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Instruments for causal inference: an epidemiologist’s dream?
M. A. Hernán and J. M. Robins · 2006
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Estimating high-dimensional directed acyclic graphs with the PC-algorithm
M. Kalisch and P. Bühlmann · 2007
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Four types of effect modification: A classification based on directed acyclic graphs
T. J. VanderWeele and J. M. Robins · 2007
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Estimating high-dimensional intervention effects from observational data
M. H. Maathuis, M. Kalisch, and P. Bühlmann · 2009
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On the validity of covariate adjustment for estimating causal effects
I. Shpitser, T. VanderWeele, and J. M. Robins · 2010
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Partition MCMC for inference on acyclic digraphs
J. Kuipers and G. Moffa · 2017
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Using directed acyclic graphs in epidemiological research in psychosis: An analysis of the role of bullying in psychosis
G. Moffa, G. Catone, J. Kuipers, E. Kuipers, D. Freeman, S. Marwaha, B. Lennox, M. Broome, and P. Bebbington · 2017
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Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs
E. Perković, J. Textor, M. Kalisch, and M. H. Maathuis · 2017
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Efficient sampling and structure learning of Bayesian networks
J. Kuipers, P. Suter, and G. Moffa · 2018
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Graphical criteria for efficient total effect estimation via adjustment in causal linear models
L. Henckel, E. Perković, and M. H. Maathuis · 2019
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Modelling in drug development, 2011
S. Senn · 2011
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A generalized back-door criterion
M. H. Maathuis and D. Colombo · 2015
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Efficient adjustment sets for population average causal treatment effect estimation in graphical models
A. Rotnitzky and E. Smucler · 2020
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On efficient adjustment in causal graphs
J. Witte, L. Henckel, M. H. Maathuis, and V. Didelez · 2020
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