Zobrazeno 1 - 10
of 186
pro vyhledávání: '"Grayling, Michael J"'
Under a generalised estimating equation analysis approach, approximate design theory is used to determine Bayesian D-optimal designs. For two examples, considering simple exchangeable and exponential decay correlation structures, we compare the effic
Externí odkaz:
http://arxiv.org/abs/2402.09938
Adaptive designs(AD) are a broad class of trial designs that allow preplanned modifications based on patient data providing improved efficiency and flexibility. However, a delay in observing the primary outcome variable can harm this added efficiency
Externí odkaz:
http://arxiv.org/abs/2306.04430
Autor:
Cherlin, Svetlana, Bigirumurame, Theophile, Grayling, Michael J, Nsengimana, Jérémie, Ouma, Luke, Santaolalla, Aida, Wan, Fang, Williamson, S Faye, Wason, James M S
Introduction: Even in effectively conducted randomised trials, the probability of a successful study remains relatively low. With recent advances in the next-generation sequencing technologies, there is a rapidly growing number of high-dimensional da
Externí odkaz:
http://arxiv.org/abs/2305.10174
Publikováno v:
Biostatistics 2022
Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit borrowing of
Externí odkaz:
http://arxiv.org/abs/2205.12227
Existing multi-outcome designs focus almost entirely on evaluating whether all outcomes show evidence of efficacy or whether at least one outcome shows evidence of efficacy. While a small number of authors have provided multi-outcome designs that eva
Externí odkaz:
http://arxiv.org/abs/2012.10194
Autor:
Kunzmann, Kevin, Grayling, Michael J., Lee, Kim M., Robertson, David S., Rufibach, Kaspar, Wason, James M. S.
Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Designs with adaptive sample size need to account for their optional stopping to guarantee strict type-I error-rate
Externí odkaz:
http://arxiv.org/abs/2010.06567
Autor:
Lv, Duo1,2 (AUTHOR), Grayling, Michael J.3 (AUTHOR), Zhang, Xinyue3 (AUTHOR), Zhao, Qingwei1,2 (AUTHOR), Zheng, Haiyan4 (AUTHOR) hz2075@bath.ac.uk
Publikováno v:
BMC Medical Research Methodology. 12/19/2023, Vol. 23 Issue 1, p1-15. 15p.
Purpose: Two-stage single-arm trial designs are commonly used in phase II oncology to infer treatment effects for a binary primary outcome (e.g., tumour response). It is imperative that such studies be designed, analysed, and reported effectively. Ho
Externí odkaz:
http://arxiv.org/abs/2007.04168
Autor:
Kunzmann, Kevin, Grayling, Michael J., Lee, Kim May, Robertson, David S., Rufibach, Kaspar, Wason, James M. S.
Publikováno v:
Am. Stat., 2021, 75(4), 424--432
Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type I error rate and a minimal desired power. Here, power depends on the u
Externí odkaz:
http://arxiv.org/abs/2006.15715
In single-arm phase II oncology trials, the most popular choice of design is Simon's two-stage design, which allows early stopping at one interim analysis. However, the expected trial sample size can be reduced further by allowing curtailment. Curtai
Externí odkaz:
http://arxiv.org/abs/1909.03017