471 related articles for article (PubMed ID: 26426943)
1. Bias Formulas for Estimating Direct and Indirect Effects When Unmeasured Confounding Is Present.
le Cessie S
Epidemiology; 2016 Jan; 27(1):125-32. PubMed ID: 26426943
[TBL] [Abstract][Full Text] [Related]
2. Quantification of bias in direct effects estimates due to different types of measurement error in the mediator.
le Cessie S; Debeij J; Rosendaal FR; Cannegieter SC; Vandenbroucke JP
Epidemiology; 2012 Jul; 23(4):551-60. PubMed ID: 22526092
[TBL] [Abstract][Full Text] [Related]
3. Two-stage instrumental variable methods for estimating the causal odds ratio: analysis of bias.
Cai B; Small DS; Have TR
Stat Med; 2011 Jul; 30(15):1809-24. PubMed ID: 21495062
[TBL] [Abstract][Full Text] [Related]
4. Bias formulas for external adjustment and sensitivity analysis of unmeasured confounders.
Arah OA; Chiba Y; Greenland S
Ann Epidemiol; 2008 Aug; 18(8):637-46. PubMed ID: 18652982
[TBL] [Abstract][Full Text] [Related]
5. Adjusting for bias and unmeasured confounding in Mendelian randomization studies with binary responses.
Palmer TM; Thompson JR; Tobin MD; Sheehan NA; Burton PR
Int J Epidemiol; 2008 Oct; 37(5):1161-8. PubMed ID: 18463132
[TBL] [Abstract][Full Text] [Related]
6. The sign of the unmeasured confounding bias under various standard populations.
Chiba Y
Biom J; 2009 Aug; 51(4):670-6. PubMed ID: 19650054
[TBL] [Abstract][Full Text] [Related]
7. A principal stratification approach for evaluating natural direct and indirect effects in the presence of treatment-induced intermediate confounding.
Taguri M; Chiba Y
Stat Med; 2015 Jan; 34(1):131-44. PubMed ID: 25312003
[TBL] [Abstract][Full Text] [Related]
8. 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. PubMed ID: 27711981
[TBL] [Abstract][Full Text] [Related]
9. 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; 174(6):710-7. PubMed ID: 21652602
[TBL] [Abstract][Full Text] [Related]
10. Misclassification of the mediator matters when estimating indirect effects.
Blakely T; McKenzie S; Carter K
J Epidemiol Community Health; 2013 May; 67(5):458-66. PubMed ID: 23386673
[TBL] [Abstract][Full Text] [Related]
11. Bounding the bias of unmeasured factors with confounding and effect-modifying potentials.
Lee WC
Stat Med; 2011 Apr; 30(9):1007-17. PubMed ID: 21472760
[TBL] [Abstract][Full Text] [Related]
12. A comparison of methods to estimate the survivor average causal effect in the presence of missing data: a simulation study.
McGuinness MB; Kasza J; Karahalios A; Guymer RH; Finger RP; Simpson JA
BMC Med Res Methodol; 2019 Dec; 19(1):223. PubMed ID: 31795945
[TBL] [Abstract][Full Text] [Related]
13. Mediation analysis in epidemiology: methods, interpretation and bias.
Richiardi L; Bellocco R; Zugna D
Int J Epidemiol; 2013 Oct; 42(5):1511-9. PubMed ID: 24019424
[TBL] [Abstract][Full Text] [Related]
14. Prior event rate ratio adjustment: numerical studies of a statistical method to address unrecognized confounding in observational studies.
Yu M; Xie D; Wang X; Weiner MG; Tannen RL
Pharmacoepidemiol Drug Saf; 2012 May; 21 Suppl 2():60-8. PubMed ID: 22552981
[TBL] [Abstract][Full Text] [Related]
15. Using generalized additive models to reduce residual confounding.
Benedetti A; Abrahamowicz M
Stat Med; 2004 Dec; 23(24):3781-801. PubMed ID: 15580601
[TBL] [Abstract][Full Text] [Related]
16. Assessing the impact of unmeasured confounding for binary outcomes using confounding functions.
Kasza J; Wolfe R; Schuster T
Int J Epidemiol; 2017 Aug; 46(4):1303-1311. PubMed ID: 28338913
[TBL] [Abstract][Full Text] [Related]
17. Hierarchical priors for bias parameters in Bayesian sensitivity analysis for unmeasured confounding.
McCandless LC; Gustafson P; Levy AR; Richardson S
Stat Med; 2012 Feb; 31(4):383-96. PubMed ID: 22253142
[TBL] [Abstract][Full Text] [Related]
18. Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation.
Groenwold RHH; Shofty I; Miočević M; van Smeden M; Klugkist I
BMC Med Res Methodol; 2018 Dec; 18(1):174. PubMed ID: 30577773
[TBL] [Abstract][Full Text] [Related]
19. Model specification and unmeasured confounders in partially ecologic analyses based on group proportions of exposed.
Björk J; Strömberg U
Scand J Work Environ Health; 2005 Jun; 31(3):184-90. PubMed ID: 15999570
[TBL] [Abstract][Full Text] [Related]
20. Indirect adjustment of relative risks of an exposure with multiple categories for an unmeasured confounder.
Lubin JH; Hauptmann M; Blair A
Ann Epidemiol; 2018 Nov; 28(11):801-807. PubMed ID: 30297163
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
