23 citations · 47 across the 6 of their papers we have counts for
6 papers
A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19
Christopher Jackson, Brian Tom, Peter Kirwan +5
We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are a…
The `how' matters: A simulation-based assessment of the potential contributions of LFD tests for school reopening in England
Kevin Kunzmann, Camilla Lingjaerde, Sheila Bird +1
During Covid-19 outbreaks, school closures are employed as part of governments' non-pharmaceutical interventions around the world to reduce the number of contacts and keep the repr…
Conditional Power and Friends: The Why and How of (Un)planned, Unblinded Sample Size Recalculations in Confirmatory Trials
Kevin Kunzmann, Michael J. Grayling, Kim M. Lee +3
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 acco…
A review of Bayesian perspectives on sample size derivation for confirmatory trials
Kevin Kunzmann, Michael J. Grayling, Kim May Lee +3
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…
Optimal adaptive two-stage designs for single-arm trial with binary endpoint
Kevin Kunzmann, Meinhard Kieser
Minimizing the number of patients exposed to potentially harmful drugs in early onco logical trials is a major concern during planning. Adaptive designs account for the inherent un…
Active Learning with Distributional Estimates
Jens Roeder, Boaz Nadler, Kevin Kunzmann +1
Active Learning (AL) is increasingly important in a broad range of applications. Two main AL principles to obtain accurate classification with few labeled data are refinement of th…