FORSS is a new formula-based super-sample framework for power and sample size calculations with win statistics on hierarchical endpoints that incorporates marginal effects and a flexible joint distribution.
Win statistics (win ratio, win odds, and net benefit) can complement one another to show the strength of the treatment effect on time-to-event outcomes
2 Pith papers cite this work. Polarity classification is still indexing.
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Framework clarifying causal estimands for longitudinal outcomes truncated by death, with Bayesian estimators; stratified average causal effect plus restricted mean survival time gives a more complete treatment effect characterisation.
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The FORSS Framework for Sample Size and Power Calculations With Win Statistics for Hierarchical Endpoints
FORSS is a new formula-based super-sample framework for power and sample size calculations with win statistics on hierarchical endpoints that incorporates marginal effects and a flexible joint distribution.
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Longitudinal Outcomes Truncated by Death: Causal Estimands and Bayesian Estimators
Framework clarifying causal estimands for longitudinal outcomes truncated by death, with Bayesian estimators; stratified average causal effect plus restricted mean survival time gives a more complete treatment effect characterisation.