267 related articles for article (PubMed ID: 32471366)
1. How are missing data in covariates handled in observational time-to-event studies in oncology? A systematic review.
Carroll OU; Morris TP; Keogh RH
BMC Med Res Methodol; 2020 May; 20(1):134. PubMed ID: 32471366
[TBL] [Abstract][Full Text] [Related]
2. Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study.
Marshall A; Altman DG; Holder RL
BMC Med Res Methodol; 2010 Dec; 10():112. PubMed ID: 21194416
[TBL] [Abstract][Full Text] [Related]
3. Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study.
Marshall A; Altman DG; Royston P; Holder RL
BMC Med Res Methodol; 2010 Jan; 10():7. PubMed ID: 20085642
[TBL] [Abstract][Full Text] [Related]
4. Multiple imputation in Cox regression when there are time-varying effects of covariates.
Keogh RH; Morris TP
Stat Med; 2018 Nov; 37(25):3661-3678. PubMed ID: 30014575
[TBL] [Abstract][Full Text] [Related]
5. The rise of multiple imputation: a review of the reporting and implementation of the method in medical research.
Hayati Rezvan P; Lee KJ; Simpson JA
BMC Med Res Methodol; 2015 Apr; 15():30. PubMed ID: 25880850
[TBL] [Abstract][Full Text] [Related]
6. Cox regression analysis with missing covariates via nonparametric multiple imputation.
Hsu CH; Yu M
Stat Methods Med Res; 2019 Jun; 28(6):1676-1688. PubMed ID: 29717943
[TBL] [Abstract][Full Text] [Related]
7. Nonlinear multiple imputation for continuous covariate within semiparametric Cox model: application to HIV data in Senegal.
Mbougua JB; Laurent C; Ndoye I; Delaporte E; Gwet H; Molinari N
Stat Med; 2013 Nov; 32(26):4651-65. PubMed ID: 23712767
[TBL] [Abstract][Full Text] [Related]
8. Estimating excess hazard ratios and net survival when covariate data are missing: strategies for multiple imputation.
Falcaro M; Nur U; Rachet B; Carpenter JR
Epidemiology; 2015 May; 26(3):421-8. PubMed ID: 25774607
[TBL] [Abstract][Full Text] [Related]
9. Dealing with missing outcome data in randomized trials and observational studies.
Groenwold RH; Donders AR; Roes KC; Harrell FE; Moons KG
Am J Epidemiol; 2012 Feb; 175(3):210-7. PubMed ID: 22262640
[TBL] [Abstract][Full Text] [Related]
10. Handling of missing data with multiple imputation in observational studies that address causal questions: protocol for a scoping review.
Mainzer R; Moreno-Betancur M; Nguyen C; Simpson J; Carlin J; Lee K
BMJ Open; 2023 Feb; 13(2):e065576. PubMed ID: 36725096
[TBL] [Abstract][Full Text] [Related]
11. Imputing missing time-dependent covariate values for the discrete time Cox model.
Murad H; Dankner R; Berlin A; Olmer L; Freedman LS
Stat Methods Med Res; 2020 Aug; 29(8):2074-2086. PubMed ID: 31680633
[TBL] [Abstract][Full Text] [Related]
12. Imputing missing covariates in time-to-event analysis within distributed research networks: A simulation study.
Li D; Wong J; Li X; Toh S; Wang R
Pharmacoepidemiol Drug Saf; 2023 Mar; 32(3):330-340. PubMed ID: 36380400
[TBL] [Abstract][Full Text] [Related]
13. Cox model with interval-censored covariate in cohort studies.
Ahn S; Lim J; Paik MC; Sacco RL; Elkind MS
Biom J; 2018 Jul; 60(4):797-814. PubMed ID: 29775990
[TBL] [Abstract][Full Text] [Related]
14. Handling missing covariate data in clinical studies in haematology.
Bonneville EF; Schetelig J; Putter H; de Wreede LC
Best Pract Res Clin Haematol; 2023 Jun; 36(2):101477. PubMed ID: 37353284
[TBL] [Abstract][Full Text] [Related]
15. Improving upon the efficiency of complete case analysis when covariates are MNAR.
Bartlett JW; Carpenter JR; Tilling K; Vansteelandt S
Biostatistics; 2014 Oct; 15(4):719-30. PubMed ID: 24907708
[TBL] [Abstract][Full Text] [Related]
16. A comparison of multiple imputation and fully augmented weighted estimators for Cox regression with missing covariates.
Qi L; Wang YF; He Y
Stat Med; 2010 Nov; 29(25):2592-604. PubMed ID: 20806403
[TBL] [Abstract][Full Text] [Related]
17. A review of the reporting and handling of missing data in cohort studies with repeated assessment of exposure measures.
Karahalios A; Baglietto L; Carlin JB; English DR; Simpson JA
BMC Med Res Methodol; 2012 Jul; 12():96. PubMed ID: 22784200
[TBL] [Abstract][Full Text] [Related]
18. Handling missing covariates in observational studies: an illustration with the assessment of prognostic factors of survival outcomes in soft-tissue or visceral sarcomas in irradiated fields (SIF).
Huchet N; Penel N; Bonvalot S; Thariat J; Ducimetière F; Giraud A; Toulmonde M; Le Cesne A; Blay JY; Bellera C
Ther Adv Med Oncol; 2024; 16():17588359231220999. PubMed ID: 38249328
[TBL] [Abstract][Full Text] [Related]
19. The type I error and power of non-parametric logrank and Wilcoxon tests with adjustment for covariates--a simulation study.
Jiang H; Symanowski J; Paul S; Qu Y; Zagar A; Hong S
Stat Med; 2008 Dec; 27(28):5850-60. PubMed ID: 18759373
[TBL] [Abstract][Full Text] [Related]
20. Missing data in FFQs: making assumptions about item non-response.
Lamb KE; Olstad DL; Nguyen C; Milte C; McNaughton SA
Public Health Nutr; 2017 Apr; 20(6):965-970. PubMed ID: 27923414
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]