87 citations · 557 across the 33 of their papers we have counts for
5 papers · 2 filters
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…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- estimation of adverse event risks
Regina Stegherr, Claudia Schmoor, Jan Beyersmann +12
The SAVVY project aims to improve the analyses of adverse event (AE) data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up tim…
Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- comparison of adverse event risks in randomized controlled trials
Kaspar Rufibach, Regina Stegherr, Claudia Schmoor +12
Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times)…
Principal Stratum Strategy: Potential Role in Drug Development
Björn Bornkamp, Kaspar Rufibach, Jianchang Lin +6
A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristi…
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…