119 related articles for article (PubMed ID: 38252651)
21. CondiS: A conditional survival distribution-based method for censored data imputation overcoming the hurdle in machine learning-based survival analysis.
Wang Y; Flowers CR; Li Z; Huang X
J Biomed Inform; 2022 Jul; 131():104117. PubMed ID: 35690348
[TBL] [Abstract][Full Text] [Related]
22. Bayesian analysis of censored response data in family-based genetic association studies.
Del Greco M F; Pattaro C; Minelli C; Thompson JR
Biom J; 2016 Sep; 58(5):1039-53. PubMed ID: 27218832
[TBL] [Abstract][Full Text] [Related]
23. Bayesian joint modeling of longitudinal measurements and time-to-event data using robust distributions.
Baghfalaki T; Ganjali M; Hashemi R
J Biopharm Stat; 2014; 24(4):834-55. PubMed ID: 24697192
[TBL] [Abstract][Full Text] [Related]
24. Power and sample size for survival analysis under the Weibull distribution when the whole lifespan is of interest.
Heo M; Faith MS; Allison DB
Mech Ageing Dev; 1998 May; 102(1):45-53. PubMed ID: 9663791
[TBL] [Abstract][Full Text] [Related]
25. Survival analysis for white non-Hispanic female breast cancer patients.
Khan HM; Saxena A; Gabbidon K; Stewart TS; Bhatt C
Asian Pac J Cancer Prev; 2014; 15(9):4049-54. PubMed ID: 24935595
[TBL] [Abstract][Full Text] [Related]
26. Simple parametric survival analysis with anonymized register data: A cohort study with truncated and interval censored event and censoring times.
Støvring H; Kristiansen IS
BMC Res Notes; 2011 Aug; 4():308. PubMed ID: 21867515
[TBL] [Abstract][Full Text] [Related]
27. A Comparison of the β-Substitution Method and a Bayesian Method for Analyzing Left-Censored Data.
Huynh T; Quick H; Ramachandran G; Banerjee S; Stenzel M; Sandler DP; Engel LS; Kwok RK; Blair A; Stewart PA
Ann Occup Hyg; 2016 Jan; 60(1):56-73. PubMed ID: 26209598
[TBL] [Abstract][Full Text] [Related]
28. A review and comparison of methods for recreating individual patient data from published Kaplan-Meier survival curves for economic evaluations: a simulation study.
Wan X; Peng L; Li Y
PLoS One; 2015; 10(3):e0121353. PubMed ID: 25803659
[TBL] [Abstract][Full Text] [Related]
29. Exponentiated Weibull regression for time-to-event data.
Khan SA
Lifetime Data Anal; 2018 Apr; 24(2):328-354. PubMed ID: 28349290
[TBL] [Abstract][Full Text] [Related]
30. Comparing Modeling Approaches for Discrete Event Simulations With Competing Risks Based on Censored Individual Patient Data: A Simulation Study and Illustration in Colorectal Cancer.
Degeling K; IJzerman MJ; Groothuis-Oudshoorn CGM; Franken MD; Koopman M; Clements MS; Koffijberg H
Value Health; 2022 Jan; 25(1):104-115. PubMed ID: 35031089
[TBL] [Abstract][Full Text] [Related]
31. A Conditional Probability Model to Predict the Mortality in Patients With Breast Cancer: A Bayesian Network Analysis.
Iraji Z; Asghari Jafarabadi M; Jafari-Koshki T; Dolatkhah R
Am J Med Sci; 2020 Nov; 360(5):575-580. PubMed ID: 32739037
[TBL] [Abstract][Full Text] [Related]
32. Bayesian methods for setting sample sizes and choosing allocation ratios in phase II clinical trials with time-to-event endpoints.
Cotterill A; Whitehead J
Stat Med; 2015 May; 34(11):1889-903. PubMed ID: 25620687
[TBL] [Abstract][Full Text] [Related]
33. Sample sizes for comparing means of two lifetime distributions with type II censored data: application in an aging intervention study.
Xiong C; Yan Y; Ji M
Control Clin Trials; 2003 Jun; 24(3):283-93. PubMed ID: 12757994
[TBL] [Abstract][Full Text] [Related]
34. Assessing accuracy of Weibull shape parameter estimate from historical studies for subsequent sample size calculation in clinical trials with time-to-event outcome.
Phadnis MA; Sharma P; Thewarapperuma N; Chalise P
Contemp Clin Trials Commun; 2020 Mar; 17():100548. PubMed ID: 32154431
[TBL] [Abstract][Full Text] [Related]
35. Power and sample size calculations for interval-censored survival analysis.
Kim HY; Williamson JM; Lin HM
Stat Med; 2016 Apr; 35(8):1390-400. PubMed ID: 26643411
[TBL] [Abstract][Full Text] [Related]
36. Analyses of cumulative incidence functions via non-parametric multiple imputation.
Ruan PK; Gray RJ
Stat Med; 2008 Nov; 27(27):5709-24. PubMed ID: 18712779
[TBL] [Abstract][Full Text] [Related]
37. Assessment and monitoring in clinical trials when survival curves have distinct shapes: a Bayesian approach with Weibull modelling.
Lecoutre B; Mabika B; Derzko G
Stat Med; 2002 Mar; 21(5):663-74. PubMed ID: 11870808
[TBL] [Abstract][Full Text] [Related]
38. On a new type of Birnbaum-Saunders models and its inference and application to fatigue data.
Arrué J; Arellano-Valle RB; Gómez HW; Leiva V
J Appl Stat; 2020; 47(13-15):2690-2710. PubMed ID: 35707422
[TBL] [Abstract][Full Text] [Related]
39. Multiple imputation based on restricted mean model for censored data.
Liu LX; Murray S; Tsodikov A
Stat Med; 2011 May; 30(12):1339-50. PubMed ID: 21560139
[TBL] [Abstract][Full Text] [Related]
40. Statistical applications for the prediction of white Hispanic breast cancer survival.
Khan HM; Saxena A; Gabbidon K; Ross E; Shrestha A
Asian Pac J Cancer Prev; 2014; 15(14):5571-5. PubMed ID: 25081666
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
