Graphical Models for Processing Missing Data

DOI10.1080/01621459.2021.1874961zbMath1464.62314arXiv1801.03583OpenAlexW3124308904MaRDI QIDQ4999179

Karthika Mohan, Judea Pearl

Publication date: 6 July 2021

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1801.03583

zbMATH Keywords

testabilitymissing datagraphical modelsnonignorablemissing not at randomrecoverability

Mathematics Subject Classification ID

Missing data (62D10) Probabilistic graphical models (62H22)

Related Items

Pattern graphs: a graphical approach to nonmonotone missing data, Semiparametric Inference for Nonmonotone Missing-Not-at-Random Data: The No Self-Censoring Model, Analysis of local sensitivity to nonignorability with missing outcomes and predictors, Nonparametric Bounds for Causal Effects in Imperfect Randomized Experiments, Ignoring non-ignorable missingness, Diagnosing and handling common violations of missing at random, Greedy structure learning from data that contain systematic missing values

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