154 related articles for article (PubMed ID: 35678168)
1. Application of quantitative bias analysis for unmeasured confounding in cost-effectiveness modelling.
Leahy TP; Duffield S; Kent S; Sammon C; Tzelis D; Ray J; Groenwold RH; Gomes M; Ramagopalan S; Grieve R
J Comp Eff Res; 2022 Aug; 11(12):861-870. PubMed ID: 35678168
[TBL] [Abstract][Full Text] [Related]
2. Quantitative bias analysis in practice: review of software for regression with unmeasured confounding.
Kawabata E; Tilling K; Groenwold RHH; Hughes RA
BMC Med Res Methodol; 2023 May; 23(1):111. PubMed ID: 37142961
[TBL] [Abstract][Full Text] [Related]
3. Unmeasured confounding in nonrandomized studies: quantitative bias analysis in health technology assessment.
Leahy TP; Kent S; Sammon C; Groenwold RH; Grieve R; Ramagopalan S; Gomes M
J Comp Eff Res; 2022 Aug; 11(12):851-859. PubMed ID: 35678151
[TBL] [Abstract][Full Text] [Related]
4. The role of quantitative bias analysis for nonrandomized comparisons in health technology assessment: recommendations from an expert workshop.
Leahy TP; Durand-Zaleski I; Sampietro-Colom L; Kent S; Zöllner Y; Coyle D; Casadei G
Int J Technol Assess Health Care; 2023 Nov; 39(1):e68. PubMed ID: 37981828
[TBL] [Abstract][Full Text] [Related]
5. Assessing Techniques for Quantifying the Impact of Bias Due to an Unmeasured Confounder: An Applied Example.
Barberio J; Ahern TP; MacLehose RF; Collin LJ; Cronin-Fenton DP; Damkier P; Sørensen HT; Lash TL
Clin Epidemiol; 2021; 13():627-635. PubMed ID: 34349564
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Assessing the impact of unmeasured confounders for credible and reliable real-world evidence.
Zhang X; Stamey JD; Mathur MB
Pharmacoepidemiol Drug Saf; 2020 Oct; 29(10):1219-1227. PubMed ID: 32929830
[TBL] [Abstract][Full Text] [Related]
8. How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies.
Barrowman MA; Peek N; Lambie M; Martin GP; Sperrin M
BMC Med Res Methodol; 2019 Jul; 19(1):166. PubMed ID: 31366331
[TBL] [Abstract][Full Text] [Related]
9. SAS and R code for probabilistic quantitative bias analysis for misclassified binary variables and binary unmeasured confounders.
Fox MP; MacLehose RF; Lash TL
Int J Epidemiol; 2023 Oct; 52(5):1624-1633. PubMed ID: 37141446
[TBL] [Abstract][Full Text] [Related]
10. Understanding the impact of non-shared unmeasured confounding on the sibling comparison analysis.
Esen BÖ; Ehrenstein V; Petersen I; Sørensen HT; Pedersen L
Int J Epidemiol; 2024 Feb; 53(1):. PubMed ID: 38110565
[TBL] [Abstract][Full Text] [Related]
11. Estimating Bias Due to Unmeasured Confounding in Oral Health Epidemiology.
Mittinty MN
Community Dent Health; 2020 Feb; 37(1):84-89. PubMed ID: 32031350
[TBL] [Abstract][Full Text] [Related]
12. 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. PubMed ID: 27576907
[TBL] [Abstract][Full Text] [Related]
13. Adjusting for unmeasured confounding in nonrandomized longitudinal studies: a methodological review.
Streeter AJ; Lin NX; Crathorne L; Haasova M; Hyde C; Melzer D; Henley WE
J Clin Epidemiol; 2017 Jul; 87():23-34. PubMed ID: 28460857
[TBL] [Abstract][Full Text] [Related]
14. The impact of unmeasured within- and between-cluster confounding on the bias of effect estimatorsof a continuous exposure.
Li Y; Lee Y; Port FK; Robinson BM
Stat Methods Med Res; 2020 Aug; 29(8):2119-2139. PubMed ID: 31694489
[TBL] [Abstract][Full Text] [Related]
15. To Adjust or Not to Adjust? When a "Confounder" Is Only Measured After Exposure.
Groenwold RHH; Palmer TM; Tilling K
Epidemiology; 2021 Mar; 32(2):194-201. PubMed ID: 33470711
[TBL] [Abstract][Full Text] [Related]
16. Mediational E-values: Approximate Sensitivity Analysis for Unmeasured Mediator-Outcome Confounding.
Smith LH; VanderWeele TJ
Epidemiology; 2019 Nov; 30(6):835-837. PubMed ID: 31348008
[TBL] [Abstract][Full Text] [Related]
17. Bias factor, maximum bias and the E-value: insight and extended applications.
Cusson A; Infante-Rivard C
Int J Epidemiol; 2020 Oct; 49(5):1509-1516. PubMed ID: 32995847
[TBL] [Abstract][Full Text] [Related]
18. Sensitivity analyses of unmeasured and partially-measured confounders using multiple imputation in a vaccine safety study.
Xu S; Clarke CL; Newcomer SR; Daley MF; Glanz JM
Pharmacoepidemiol Drug Saf; 2021 Sep; 30(9):1200-1213. PubMed ID: 33988275
[TBL] [Abstract][Full Text] [Related]
19. [How to adjust confounders in studies on observational comparative effectiveness: (3) approaches on sensitivity analysis for confounder adjustment].
Huang LL; Zhao Y; Wei YY; Chen F
Zhonghua Liu Xing Bing Xue Za Zhi; 2019 Dec; 40(12):1645-1649. PubMed ID: 32062931
[TBL] [Abstract][Full Text] [Related]
20. Quantitative bias analysis for external control arms using real-world data in clinical trials: a primer for clinical researchers.
Thorlund K; Duffield S; Popat S; Ramagopalan S; Gupta A; Hsu G; Arora P; Subbiah V
J Comp Eff Res; 2024 Mar; 13(3):e230147. PubMed ID: 38205741
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
