Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting-Reference-Cited by-同舟云学术

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Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting

Published:2018-07-03 Issue:1 Volume:18 Page:
ISSN:1471-2288
Container-title:BMC Medical Research Methodology
language:en
Short-container-title:BMC Med Res Methodol

Author:

Asvatourian Vahé,Coutzac Clélia,Chaput Nathalie,Robert Caroline,Michiels Stefan,Lanoy Emilie

Funder

Institut National Du Cancer

Institut Gustave-Roussy (FR)

Institut National de la Santé et de la Recherche Médicale

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Epidemiology

Link

http://link.springer.com/content/pdf/10.1186/s12874-018-0527-5.pdf

Reference29 articles.

1. Maathuis MH, Kalisch M, Bühlmann P. Estimating high-dimensional intervention effects from observational data. Ann Stat. 2009;37(6 A):3133–64.

2. Spirtes P, Glymour C, Scheines R. Causation, Prediction, and Search. New York: Springer Verlag; 1993.

3. Pearl J. Causality: Models, Reasoning, and Inference. 2nd ed. Cambridge: Cambridge University Press; 2009.

4. Robins JM, Hernán MÁ, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11:550–60.

5. Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology. 2000;11:561–70.

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3. Integrating expert’s knowledge constraint of time dependent exposures in structure learning for Bayesian networks;Artificial Intelligence in Medicine;2020-07

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