261 related articles for article (PubMed ID: 30014575)
1. 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]
2. Dealing with missing information on covariates for excess mortality hazard regression models - Making the imputation model compatible with the substantive model.
Antunes L; Mendonça D; Bento MJ; Njagi EN; Belot A; Rachet B
Stat Methods Med Res; 2021 Oct; 30(10):2256-2268. PubMed ID: 34473604
[TBL] [Abstract][Full Text] [Related]
3. Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model.
Bartlett JW; Seaman SR; White IR; Carpenter JR;
Stat Methods Med Res; 2015 Aug; 24(4):462-87. PubMed ID: 24525487
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. 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]
7. Multiple imputation of missing covariates for the Cox proportional hazards cure model.
Beesley LJ; Bartlett JW; Wolf GT; Taylor JM
Stat Med; 2016 Nov; 35(26):4701-4717. PubMed ID: 27439726
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study.
De Silva AP; Moreno-Betancur M; De Livera AM; Lee KJ; Simpson JA
BMC Med Res Methodol; 2019 Jan; 19(1):14. PubMed ID: 30630434
[TBL] [Abstract][Full Text] [Related]
10. Multiple imputation of missing data in nested case-control and case-cohort studies.
Keogh RH; Seaman SR; Bartlett JW; Wood AM
Biometrics; 2018 Dec; 74(4):1438-1449. PubMed ID: 29870056
[TBL] [Abstract][Full Text] [Related]
11. Multiple imputation for handling missing outcome data when estimating the relative risk.
Sullivan TR; Lee KJ; Ryan P; Salter AB
BMC Med Res Methodol; 2017 Sep; 17(1):134. PubMed ID: 28877666
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Missing covariates in competing risks analysis.
Bartlett JW; Taylor JM
Biostatistics; 2016 Oct; 17(4):751-63. PubMed ID: 27179002
[TBL] [Abstract][Full Text] [Related]
14. Unified estimation for Cox regression model with nonmonotone missing at random covariates.
Thiessen DL; Zhao Y; Tu D
Stat Med; 2022 Oct; 41(24):4781-4790. PubMed ID: 35788969
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. Multiple imputation for cause-specific Cox models: Assessing methods for estimation and prediction.
Bonneville EF; Resche-Rigon M; Schetelig J; Putter H; de Wreede LC
Stat Methods Med Res; 2022 Oct; 31(10):1860-1880. PubMed ID: 35658734
[TBL] [Abstract][Full Text] [Related]
18. Imputing missing covariate values for the Cox model.
White IR; Royston P
Stat Med; 2009 Jul; 28(15):1982-98. PubMed ID: 19452569
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Using fractional polynomials and restricted cubic splines to model non-proportional hazards or time-varying covariate effects in the Cox regression model.
Austin PC; Fang J; Lee DS
Stat Med; 2022 Feb; 41(3):612-624. PubMed ID: 34806210
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
