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Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting

American journal of epidemiology, 2015-03, Vol.181 (5), p.349-356 [Peer Reviewed Journal]

The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. ;Copyright Oxford Publishing Limited(England) Mar 1, 2015 ;The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2015 ;ISSN: 0002-9262 ;EISSN: 1476-6256 ;DOI: 10.1093/aje/kwu278 ;PMID: 25693776

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  • Title:
    Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting
  • Author: Nguyen, Quynh C ; Osypuk, Theresa L ; Schmidt, Nicole M ; Glymour, M Maria ; Tchetgen Tchetgen, Eric J
  • Subjects: Causality ; Epidemiologic Methods ; Housing - statistics & numerical data ; Humans ; Mediation ; Mediators ; Neighborhoods ; Obesity ; Obesity - epidemiology ; Odds Ratio ; Practice of Epidemiology ; Prevalence ; Randomized Controlled Trials as Topic ; Regression Analysis ; Residence Characteristics ; Vouchers
  • Is Part Of: American journal of epidemiology, 2015-03, Vol.181 (5), p.349-356
  • Description: Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994-2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided.
  • Publisher: United States: Oxford Publishing Limited (England)
  • Language: English
  • Identifier: ISSN: 0002-9262
    EISSN: 1476-6256
    DOI: 10.1093/aje/kwu278
    PMID: 25693776
  • Source: GFMER Free Medical Journals
    MEDLINE
    Alma/SFX Local Collection
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