Invited commentary: Agent-based models for causal inference—reweighting data and theory in epidemiology.

Abstract:

:The relative weights of empirical facts (data) and assumptions (theory) in causal inference vary across disciplines. Typically, disciplines that ask more complex questions tend to better tolerate a greater role of theory and modeling in causal inference. As epidemiologists move toward increasingly complex questions, Marshall and Galea (Am J Epidemiol. 2015;181(2):92-99) support a reweighting of data and theory in epidemiologic research via the use of agent-based modeling. The parametric g-formula can be viewed as an intermediate step between traditional epidemiologic methods and agent-based modeling and therefore is a method that can ease the transition toward epidemiologic methods that rely heavily on modeling.

journal_name

Am J Epidemiol

authors

Hernán MA

doi

10.1093/aje/kwu272

subject

Has Abstract

pub_date

2015-01-15 00:00:00

pages

103-5

issue

2

eissn

0002-9262

issn

1476-6256

pii

kwu272

journal_volume

181

pub_type

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