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Items: 1 to 20 of 105

1.

Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications.

Lutz SM, Thwing A, Schmiege S, Kroehl M, Baker CD, Starling AP, Hokanson JE, Ghosh D.

BMC Bioinformatics. 2017 Jul 19;18(1):344. doi: 10.1186/s12859-017-1749-y.

2.

Bayesian sensitivity analysis for unmeasured confounding in causal mediation analysis.

McCandless LC, Somers JM.

Stat Methods Med Res. 2019 Feb;28(2):515-531. doi: 10.1177/0962280217729844. Epub 2017 Sep 7.

PMID:
28882092
3.

Sensitivity analysis for the effects of multiple unmeasured confounders.

Groenwold RH, Sterne JA, Lawlor DA, Moons KG, Hoes AW, Tilling K.

Ann Epidemiol. 2016 Sep;26(9):605-11. doi: 10.1016/j.annepidem.2016.07.009. Epub 2016 Aug 3.

PMID:
27576907
4.

Bias Formulas for Estimating Direct and Indirect Effects When Unmeasured Confounding Is Present.

le Cessie S.

Epidemiology. 2016 Jan;27(1):125-32. doi: 10.1097/EDE.0000000000000407.

PMID:
26426943
5.

The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study.

Fewell Z, Davey Smith G, Sterne JA.

Am J Epidemiol. 2007 Sep 15;166(6):646-55. Epub 2007 Jul 5.

PMID:
17615092
6.

A sensitivity analysis using information about measured confounders yielded improved uncertainty assessments for unmeasured confounding.

McCandless LC, Gustafson P, Levy AR.

J Clin Epidemiol. 2008 Mar;61(3):247-55. doi: 10.1016/j.jclinepi.2007.05.006. Epub 2007 Oct 15.

PMID:
18226747
7.

Assessing the impact of unmeasured confounding for binary outcomes using confounding functions.

Kasza J, Wolfe R, Schuster T.

Int J Epidemiol. 2017 Aug 1;46(4):1303-1311. doi: 10.1093/ije/dyx023.

PMID:
28338913
8.

Assessing mediation using marginal structural models in the presence of confounding and moderation.

Coffman DL, Zhong W.

Psychol Methods. 2012 Dec;17(4):642-64. doi: 10.1037/a0029311. Epub 2012 Aug 20.

9.

Assessing moderated mediation in linear models requires fewer confounding assumptions than assessing mediation.

Loeys T, Talloen W, Goubert L, Moerkerke B, Vansteelandt S.

Br J Math Stat Psychol. 2016 Nov;69(3):352-374. doi: 10.1111/bmsp.12077.

PMID:
27711981
10.

Sensitivity analysis for unobserved confounding of direct and indirect effects using uncertainty intervals.

Lindmark A, de Luna X, Eriksson M.

Stat Med. 2018 May 10;37(10):1744-1762. doi: 10.1002/sim.7620. Epub 2018 Feb 20.

PMID:
29462839
11.

Mediation Analysis: A Practitioner's Guide.

VanderWeele TJ.

Annu Rev Public Health. 2016;37:17-32. doi: 10.1146/annurev-publhealth-032315-021402. Epub 2015 Nov 30. Review.

PMID:
26653405
12.

Measurement error, time lag, unmeasured confounding: Considerations for longitudinal estimation of the effect of a mediator in randomised clinical trials.

Goldsmith KA, Chalder T, White PD, Sharpe M, Pickles A.

Stat Methods Med Res. 2018 Jun;27(6):1615-1633. doi: 10.1177/0962280216666111. Epub 2016 Sep 19.

13.

Method for evaluating multiple mediators: mediating effects of smoking and COPD on the association between the CHRNA5-A3 variant and lung cancer risk.

Wang J, Spitz MR, Amos CI, Wu X, Wetter DW, Cinciripini PM, Shete S.

PLoS One. 2012;7(10):e47705. doi: 10.1371/journal.pone.0047705. Epub 2012 Oct 15.

14.

Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures.

Brumback BA, HernĂ¡n MA, Haneuse SJ, Robins JM.

Stat Med. 2004 Mar 15;23(5):749-67.

PMID:
14981673
15.

Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding.

Ding P, Vanderweele TJ.

Biometrika. 2016 Jun;103(2):483-490. Epub 2016 Apr 30.

16.

Assessing the sensitivity of regression results to unmeasured confounders in observational studies.

Lin DY, Psaty BM, Kronmal RA.

Biometrics. 1998 Sep;54(3):948-63.

PMID:
9750244
17.

Sensitivity analysis for unmeasured confounders using an electronic spreadsheet.

Cabral MD, Luiz RR.

Rev Saude Publica. 2007 Jun;41(3):446-52.

18.

Mediating effects of smoking and chronic obstructive pulmonary disease on the relation between the CHRNA5-A3 genetic locus and lung cancer risk.

Wang J, Spitz MR, Amos CI, Wilkinson AV, Wu X, Shete S.

Cancer. 2010 Jul 15;116(14):3458-62. doi: 10.1002/cncr.25085.

19.

Confounding of indirect effects: a sensitivity analysis exploring the range of bias due to a cause common to both the mediator and the outcome.

Hafeman DM.

Am J Epidemiol. 2011 Sep 15;174(6):710-7. doi: 10.1093/aje/kwr173. Epub 2011 Jun 7.

PMID:
21652602
20.

Occupational exposures and lung cancer: adjustment for unmeasured confounding by smoking.

Richardson DB.

Epidemiology. 2010 Mar;21(2):181-6. doi: 10.1097/EDE.0b013e3181c6f7d9.

PMID:
20081541

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