143 related articles for article (PubMed ID: 34817733)
1. Joint modelling with competing risks of dropout for longitudinal analysis of health-related quality of life in cancer clinical trials.
Cuer B; Conroy T; Juzyna B; Gourgou S; Mollevi C; Touraine C
Qual Life Res; 2022 May; 31(5):1359-1370. PubMed ID: 34817733
[TBL] [Abstract][Full Text] [Related]
2. Handling informative dropout in longitudinal analysis of health-related quality of life: application of three approaches to data from the esophageal cancer clinical trial PRODIGE 5/ACCORD 17.
Cuer B; Mollevi C; Anota A; Charton E; Juzyna B; Conroy T; Touraine C
BMC Med Res Methodol; 2020 Sep; 20(1):223. PubMed ID: 32883216
[TBL] [Abstract][Full Text] [Related]
3. Modelling variable dropout in randomised controlled trials with longitudinal outcomes: application to the MAGNETIC study.
Kolamunnage-Dona R; Powell C; Williamson PR
Trials; 2016 Apr; 17(1):222. PubMed ID: 27125779
[TBL] [Abstract][Full Text] [Related]
4. Flexible modeling of longitudinal health-related quality of life data accounting for informative dropout in a cancer clinical trial.
Winter A; Cuer B; Conroy T; Juzyna B; Gourgou S; Mollevi C; Touraine C
Qual Life Res; 2023 Mar; 32(3):669-679. PubMed ID: 36115002
[TBL] [Abstract][Full Text] [Related]
5. When a joint model should be preferred over a linear mixed model for analysis of longitudinal health-related quality of life data in cancer clinical trials.
Touraine C; Cuer B; Conroy T; Juzyna B; Gourgou S; Mollevi C
BMC Med Res Methodol; 2023 Feb; 23(1):36. PubMed ID: 36765307
[TBL] [Abstract][Full Text] [Related]
6. A SAS macro for the joint modeling of longitudinal outcomes and multiple competing risk dropouts.
Wang W; Wang W; Mosley TH; Griswold ME
Comput Methods Programs Biomed; 2017 Jan; 138():23-30. PubMed ID: 27886712
[TBL] [Abstract][Full Text] [Related]
7. Joint modeling of multivariate longitudinal data and the dropout process in a competing risk setting: application to ICU data.
Deslandes E; Chevret S
BMC Med Res Methodol; 2010 Jul; 10():69. PubMed ID: 20670425
[TBL] [Abstract][Full Text] [Related]
8. Modelling placebo response in depression trials using a longitudinal model with informative dropout.
Gomeni R; Lavergne A; Merlo-Pich E
Eur J Pharm Sci; 2009 Jan; 36(1):4-10. PubMed ID: 19041717
[TBL] [Abstract][Full Text] [Related]
9. Biased estimation with shared parameter models in the presence of competing dropout mechanisms.
Vonesh EF; Greene T
Biometrics; 2022 Mar; 78(1):399-406. PubMed ID: 33592109
[TBL] [Abstract][Full Text] [Related]
10. Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.
Chan JS
Biom J; 2016 May; 58(3):549-69. PubMed ID: 26467236
[TBL] [Abstract][Full Text] [Related]
11. Modelling and simulation of the Positive and Negative Syndrome Scale (PANSS) time course and dropout hazard in placebo arms of schizophrenia clinical trials.
Pilla Reddy V; Kozielska M; Johnson M; Suleiman AA; Vermeulen A; Liu J; de Greef R; Groothuis GM; Danhof M; Proost JH
Clin Pharmacokinet; 2012 Apr; 51(4):261-75. PubMed ID: 22420580
[TBL] [Abstract][Full Text] [Related]
12. Performance of nonlinear mixed effects models in the presence of informative dropout.
Björnsson MA; Friberg LE; Simonsson US
AAPS J; 2015 Jan; 17(1):245-55. PubMed ID: 25421458
[TBL] [Abstract][Full Text] [Related]
13. Testing for the presence of multiple sources of informative dropout in longitudinal data.
Crawford SB; Hanfelt JJ
Stat Med; 2008 Sep; 27(21):4175-89. PubMed ID: 18613222
[TBL] [Abstract][Full Text] [Related]
14. A joint model for nonlinear longitudinal data with informative dropout.
Hu C; Sale ME
J Pharmacokinet Pharmacodyn; 2003 Feb; 30(1):83-103. PubMed ID: 12800808
[TBL] [Abstract][Full Text] [Related]
15. An approach to joint analysis of longitudinal measurements and competing risks failure time data.
Elashoff RM; Li G; Li N
Stat Med; 2007 Jun; 26(14):2813-35. PubMed ID: 17124698
[TBL] [Abstract][Full Text] [Related]
16. Pattern mixture models and latent class models for the analysis of multivariate longitudinal data with informative dropouts.
Dantan E; Proust-Lima C; Letenneur L; Jacqmin-Gadda H
Int J Biostat; 2008; 4(1):Article 14. PubMed ID: 22462120
[TBL] [Abstract][Full Text] [Related]
17. Shared parameter and copula models for analysis of semicontinuous longitudinal data with nonrandom dropout and informative censoring.
Jaffa MA; Gebregziabher M; Jaffa AA
Stat Methods Med Res; 2022 Mar; 31(3):451-474. PubMed ID: 34806502
[TBL] [Abstract][Full Text] [Related]
18. Accommodating informative dropout and death: a joint modelling approach for longitudinal and semi-competing risks data.
Li Q; Su L
J R Stat Soc Ser C Appl Stat; 2018 Jan; 67(1):145-163. PubMed ID: 29277843
[TBL] [Abstract][Full Text] [Related]
19. Longitudinal quantile regression in the presence of informative dropout through longitudinal-survival joint modeling.
Farcomeni A; Viviani S
Stat Med; 2015 Mar; 34(7):1199-213. PubMed ID: 25488110
[TBL] [Abstract][Full Text] [Related]
20. A sensitivity analysis approach for informative dropout using shared parameter models.
Su L; Li Q; Barrett JK; Daniels MJ
Biometrics; 2019 Sep; 75(3):917-926. PubMed ID: 30666621
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]