13 citations · 45 across the 10 of their papers we have counts for
6 papers · 1 filter
Point estimation for adaptive trial designs II: practical considerations and guidance
David S. Robertson, Babak Choodari-Oskooei, Munya Dimairo +3
In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. As…
Online multiple hypothesis testing
David S. Robertson, James M. S. Wason, Aaditya Ramdas
Modern data analysis frequently involves large-scale hypothesis testing, which naturally gives rise to the problem of maintaining control of a suitable type I error rate, such as t…
Online FDR Control for RNAseq Data
Lathan Liou, Milena Hornburg, David S. Robertson
Motivation: While the analysis of a single RNA sequencing (RNAseq) dataset has been well described in the literature, modern research workflows often have additional complexity in…
Some performance considerations when using multi-armed bandit algorithms in the presence of missing data
Xijin Chen, Kim May Lee, Sofia S. Villar +1
When comparing the performance of multi-armed bandit algorithms, the potential impact of missing data is often overlooked. In practice, it also affects their implementation where t…
Familywise error rate control for block response-adaptive randomization
Ekkehard Glimm, David Robertson
Response-adaptive randomization allows the probabilities of allocating patients to treatments in a clinical trial to change based on the previously observed response data, in order…
Online error control for platform trials
David S. Robertson, James M. S. Wason, Franz König +2
Platform trials evaluate multiple experimental treatments under a single master protocol, where new treatment arms are added to the trial over time. Given the multiple treatment co…