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Inverse odds ratio-weighted estimation for causal mediation analysis
Statistics in medicine, 2013-11, Vol.32 (26), p.4567-4580
[Peer Reviewed Journal]
Copyright © 2013 John Wiley & Sons, Ltd. ;ISSN: 0277-6715 ;EISSN: 1097-0258 ;DOI: 10.1002/sim.5864 ;PMID: 23744517 ;CODEN: SMEDDA
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Title:
Inverse odds ratio-weighted estimation for causal mediation analysis
Author:
Tchetgen Tchetgen, Eric J.
Subjects:
causal mediation analysis
;
double robustness
;
Estimating techniques
;
Generalized linear models
;
Humans
;
inverse odds ratio-weighted estimation
;
Models, Statistical
;
natural direct and indirect effects
;
Odds Ratio
;
Regression analysis
;
Social sciences
;
Software
Is Part Of:
Statistics in medicine, 2013-11, Vol.32 (26), p.4567-4580
Description:
An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio‐weighted approach to estimate so‐called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.
Publisher:
England: Blackwell Publishing Ltd
Language:
English
Identifier:
ISSN: 0277-6715
EISSN: 1097-0258
DOI: 10.1002/sim.5864
PMID: 23744517
CODEN: SMEDDA
Source:
MEDLINE
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