334 related articles for article (PubMed ID: 32252820)
1. A simulation study comparing the power of nine tests of the treatment effect in randomized controlled trials with a time-to-event outcome.
Royston P; B Parmar MK
Trials; 2020 Apr; 21(1):315. PubMed ID: 32252820
[TBL] [Abstract][Full Text] [Related]
2. Comparison of survival distributions in clinical trials: A practical guidance.
Chen X; Wang X; Chen K; Zheng Y; Chappell RJ; Dey J
Clin Trials; 2020 Oct; 17(5):507-521. PubMed ID: 32594788
[TBL] [Abstract][Full Text] [Related]
3. Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated.
Royston P; Parmar MK
BMC Med Res Methodol; 2016 Feb; 16():16. PubMed ID: 26869168
[TBL] [Abstract][Full Text] [Related]
4. Combined test versus logrank/Cox test in 50 randomised trials.
Royston P; Choodari-Oskooei B; Parmar MKB; Rogers JK
Trials; 2019 Mar; 20(1):172. PubMed ID: 30885277
[TBL] [Abstract][Full Text] [Related]
5. Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study.
Jachno K; Heritier S; Wolfe R
BMC Med Res Methodol; 2021 Aug; 21(1):177. PubMed ID: 34454428
[TBL] [Abstract][Full Text] [Related]
6. An approach to trial design and analysis in the era of non-proportional hazards of the treatment effect.
Royston P; Parmar MK
Trials; 2014 Aug; 15():314. PubMed ID: 25098243
[TBL] [Abstract][Full Text] [Related]
7. Using the geometric average hazard ratio in sample size calculation for time-to-event data with composite endpoints.
Cortés Martínez J; Geskus RB; Kim K; Melis GG
BMC Med Res Methodol; 2021 May; 21(1):99. PubMed ID: 33957892
[TBL] [Abstract][Full Text] [Related]
8. Are non-constant rates and non-proportional treatment effects accounted for in the design and analysis of randomised controlled trials? A review of current practice.
Jachno K; Heritier S; Wolfe R
BMC Med Res Methodol; 2019 May; 19(1):103. PubMed ID: 31096924
[TBL] [Abstract][Full Text] [Related]
9. The Average Hazard Ratio - A Good Effect Measure for Time-to-event Endpoints when the Proportional Hazard Assumption is Violated?
Rauch G; Brannath W; Brückner M; Kieser M
Methods Inf Med; 2018 May; 57(3):89-100. PubMed ID: 29719915
[TBL] [Abstract][Full Text] [Related]
10. Sample size calculation for the combination test under nonproportional hazards.
Cheng H; He J
Biom J; 2023 Apr; 65(4):e2100403. PubMed ID: 36789566
[TBL] [Abstract][Full Text] [Related]
11. A clinical trial design using the concept of proportional time using the generalized gamma ratio distribution.
Phadnis MA; Wetmore JB; Mayo MS
Stat Med; 2017 Nov; 36(26):4121-4140. PubMed ID: 28815655
[TBL] [Abstract][Full Text] [Related]
12. Sample size calculation for the augmented logrank test in randomized clinical trials.
Hattori S; Komukai S; Friede T
Stat Med; 2022 Jun; 41(14):2627-2644. PubMed ID: 35319100
[TBL] [Abstract][Full Text] [Related]
13. Sample size calculation for two-arm trials with time-to-event endpoint for nonproportional hazards using the concept of Relative Time when inference is built on comparing Weibull distributions.
Phadnis MA; Mayo MS
Biom J; 2021 Oct; 63(7):1406-1433. PubMed ID: 34272897
[TBL] [Abstract][Full Text] [Related]
14. Empirical power comparison of statistical tests in contemporary phase III randomized controlled trials with time-to-event outcomes in oncology.
Horiguchi M; Hassett MJ; Uno H
Clin Trials; 2020 Dec; 17(6):597-606. PubMed ID: 32933339
[TBL] [Abstract][Full Text] [Related]
15. Improved logrank-type tests for survival data using adaptive weights.
Yang S; Prentice R
Biometrics; 2010 Mar; 66(1):30-8. PubMed ID: 19397582
[TBL] [Abstract][Full Text] [Related]
16. Subgroup analyses in randomised controlled trials: quantifying the risks of false-positives and false-negatives.
Brookes ST; Whitley E; Peters TJ; Mulheran PA; Egger M; Davey Smith G
Health Technol Assess; 2001; 5(33):1-56. PubMed ID: 11701102
[TBL] [Abstract][Full Text] [Related]
17. An omnibus test for several hazard alternatives in prevention randomized controlled clinical trials.
Garès V; Andrieu S; Dupuy JF; Savy N
Stat Med; 2015 Feb; 34(4):541-57. PubMed ID: 25388274
[TBL] [Abstract][Full Text] [Related]
18. Delayed treatment effects, treatment switching and heterogeneous patient populations: How to design and analyze RCTs in oncology.
Ristl R; Ballarini NM; Götte H; Schüler A; Posch M; König F
Pharm Stat; 2021 Jan; 20(1):129-145. PubMed ID: 32830428
[TBL] [Abstract][Full Text] [Related]
19. Weighted logrank tests for interval censored data when assessment times depend on treatment.
Fay MP; Shih JH
Stat Med; 2012 Dec; 31(28):3760-72. PubMed ID: 22786795
[TBL] [Abstract][Full Text] [Related]
20. Gaining power and precision by using model-based weights in the analysis of late stage cancer trials with substantial treatment switching.
Bowden J; Seaman S; Huang X; White IR
Stat Med; 2016 Apr; 35(9):1423-40. PubMed ID: 26576494
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
