A Note on G-Estimation of Causal Risk Ratios.

Abstract:

:G-estimation is a flexible, semiparametric approach for estimating exposure effects in epidemiologic studies. It has several underappreciated advantages over other propensity score-based methods popular in epidemiology, which we review in this article. However, it is rarely used in practice, due to a lack of off-the-shelf software. To rectify this, we show a simple trick for obtaining G-estimators of causal risk ratios using existing generalized estimating equations software. We extend the procedure to more complex settings with time-varying confounders.

journal_name

Am J Epidemiol

authors

Dukes O,Vansteelandt S

doi

10.1093/aje/kwx347

subject

Has Abstract

pub_date

2018-05-01 00:00:00

pages

1079-1084

issue

5

eissn

0002-9262

issn

1476-6256

pii

4930819

journal_volume

187

pub_type

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