
Discussion of 'Estimating timevarying causal excursion effect in mobile health with binary outcomes' by T. Qian et al
We discuss the recent paper on "excursion effect" by T. Qian et al. (202...
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An Interventionist Approach to Mediation Analysis
Judea Pearl's insight that, when errors are assumed independent, the Pur...
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Multivariate Counterfactual Systems And Causal Graphical Models
Among Judea Pearl's many contributions to Causality and Statistics, the ...
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Estimation of local treatment under the binary instrumental variable model
Instrumental variables are widely used to deal with unmeasured confoundi...
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Chernofftype Concentration of Empirical Probabilities in Relative Entropy
We study the relative entropy of the empirical probability vector with r...
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Empirical Bayes for Largescale Randomized Experiments: a Spectral Approach
Largescale randomized experiments, sometimes called A/B tests, are incr...
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On Testing Marginal versus Conditional Independence
We consider testing marginal independence versus conditional independenc...
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Multiplicative Effect Modeling: The General Case
Generalized linear models, such as logistic regression, are widely used ...
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A factorization criterion for acyclic directed mixed graphs
Acyclic directed mixed graphs, also known as semiMarkov models represen...
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Sparse Nested Markov models with Loglinear Parameters
Hidden variables are ubiquitous in practical data analysis, and therefor...
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A Discovery Algorithm for Directed Cyclis Graphs
Directed acyclic graphs have been used fruitfully to represent causal st...
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Crosscovariance modelling via DAGs with hidden variables
DAG models with hidden variables present many difficulties that are not ...
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Markov Equivalence Classes for Maximal Ancestral Graphs
Ancestral graphs are a class of graphs that encode conditional independe...
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A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence
Graphical models with bidirected edges (<>) represent marginal indepen...
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Using the structure of dconnecting paths as a qualitative measure of the strength of dependence
Pearls concept OF a d  connecting path IS one OF the foundations OF the...
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Proceedings of the TwentySecond Conference on Uncertainty in Artificial Intelligence (2006)
This is the Proceedings of the TwentySecond Conference on Uncertainty i...
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Parameter and Structure Learning in Nested Markov Models
The constraints arising from DAG models with latent variables can be nat...
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Iterative Conditional Fitting for Gaussian Ancestral Graph Models
Ancestral graph models, introduced by Richardson and Spirtes (2002), gen...
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Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables
It is well known that there may be many causal explanations that are con...
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Maximum likelihood fitting of acyclic directed mixed graphs to binary data
Acyclic directed mixed graphs, also known as semiMarkov models represen...
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An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models
Probabilistic inference in graphical models is the task of computing mar...
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Thomas S. Richardson
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Professor and Chair of the Department of Statistics at University of Washington