Confounding of indirect effects: a sensitivity analysis exploring the range of bias due to a cause common to both the mediator and the outcome
- PMID: 21652602
- DOI: 10.1093/aje/kwr173
Confounding of indirect effects: a sensitivity analysis exploring the range of bias due to a cause common to both the mediator and the outcome
Abstract
Several investigators have demonstrated that the assessment of indirect and direct effects is biased in the presence of a cause that is common to both the mediator and the outcome if one has not controlled for this variable in the analysis. However, little work has been done to quantify the bias caused by this type of unmeasured confounding and determine whether this bias will materially affect conclusions regarding mediation. The author developed a sensitivity analysis program to address this crucial issue. Data from 2 well-known studies in the methodological literature on mediation were reanalyzed using this program. The results of mediation analyses were found not to be as vulnerable to the impact of confounding as previously described; however, these findings varied sharply between the 2 studies. Although the indirect effect observed in one study could potentially be due to a cause common to both the mediator and the outcome, such confounding could not feasibly explain the results of the other study. These disparate results demonstrate the utility of the current sensitivity analysis when assessing mediation.
Similar articles
-
Misclassification of the mediator matters when estimating indirect effects.J Epidemiol Community Health. 2013 May;67(5):458-66. doi: 10.1136/jech-2012-201813. Epub 2013 Mar 16. J Epidemiol Community Health. 2013. PMID: 23386673
-
Mediation analysis in epidemiology: methods, interpretation and bias.Int J Epidemiol. 2013 Oct;42(5):1511-9. doi: 10.1093/ije/dyt127. Epub 2013 Sep 9. Int J Epidemiol. 2013. PMID: 24019424 Review.
-
A sensitivity analysis using information about measured confounders yielded improved uncertainty assessments for unmeasured confounding.J Clin Epidemiol. 2008 Mar;61(3):247-55. doi: 10.1016/j.jclinepi.2007.05.006. Epub 2007 Oct 15. J Clin Epidemiol. 2008. PMID: 18226747
-
Adjusting for bias and unmeasured confounding in Mendelian randomization studies with binary responses.Int J Epidemiol. 2008 Oct;37(5):1161-8. doi: 10.1093/ije/dyn080. Epub 2008 May 7. Int J Epidemiol. 2008. PMID: 18463132
-
Quantitative assessment of unobserved confounding is mandatory in nonrandomized intervention studies.J Clin Epidemiol. 2009 Jan;62(1):22-8. doi: 10.1016/j.jclinepi.2008.02.011. Epub 2008 Jul 10. J Clin Epidemiol. 2009. PMID: 18619797 Review.
Cited by
-
The explanatory role of stroke as a mediator of the mortality risk difference between older adults who initiate first- versus second-generation antipsychotic drugs.Am J Epidemiol. 2014 Oct 15;180(8):847-52. doi: 10.1093/aje/kwu210. Epub 2014 Sep 18. Am J Epidemiol. 2014. PMID: 25234432 Free PMC article.
-
Author's reply: The role of potential outcomes thinking in assessing mediation and interaction.Int J Epidemiol. 2016 Dec 1;45(6):1922-1926. doi: 10.1093/ije/dyw280. Int J Epidemiol. 2016. PMID: 27864414 Free PMC article. No abstract available.
-
Psychosocial and socioeconomic determinants of cardiovascular mortality in Eastern Europe: A multicentre prospective cohort study.PLoS Med. 2017 Dec 6;14(12):e1002459. doi: 10.1371/journal.pmed.1002459. eCollection 2017 Dec. PLoS Med. 2017. PMID: 29211726 Free PMC article.
-
Socioeconomic status, health-related behaviours, and death among older people: the Concord health and aging in men project prospective cohort study.BMC Geriatr. 2020 Jul 29;20(1):261. doi: 10.1186/s12877-020-01648-y. BMC Geriatr. 2020. PMID: 32727399 Free PMC article.
-
Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease.Int J Epidemiol. 2012 Feb;41(1):161-76. doi: 10.1093/ije/dyr233. Int J Epidemiol. 2012. PMID: 22422451 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources