A Comparison of Agent-Based Models and the Parametric G-Formula for Causal Inference

Decision-making requires choosing from treatments on the basis of correctly estimated outcome distributions under each treatment. In the absence of randomized trials, 2 possible approaches are the parametric g-formula and agent-based models (ABMs). The g-formula has been used exclusively to estimate...

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Veröffentlicht in:	American journal of epidemiology Jg. 186; H. 2; S. 131
Hauptverfasser:	Murray, Eleanor J, Robins, James M, Seage, George R, Freedberg, Kenneth A, Hernán, Miguel A
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 15.07.2017
Schlagworte:	Bias Causality Cause of Death - trends Computer Simulation - statistics & numerical data Data Interpretation, Statistical Decision Making Epidemiologic Research Design Humans Models, Statistical Monte Carlo Method Outcome Assessment, Health Care - methods Outcome Assessment, Health Care - statistics & numerical data Risk Assessment - methods Systems Analysis Monte Carlo methods agent-based models decision analysis mathematical models medical decision making causal inference individual-level models parametric g-formula
ISSN:	1476-6256, 1476-6256
Online-Zugang:	Weitere Angaben
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