科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Studies in health technology and informatics2026-09-17

WREstimates: An R Package for Win-Ratio Sample Size and Power Calculations.

Autumn Johnson

一句话结论 · In one sentence

These methods enable the calculation of sample size and power based on estimands or pilot data, thereby eliminating the need for complex simulation-based methods that require numerous assumptions about the data.

原始摘要(英文原文)· Original abstract
INTRODUCTION: The win-ratio has great potential for determining the overall efficacy of treatments and therapies in clinical trials, as its ability to hierarchically account for multiple endpoints provides a holistic metric of the treatment effect. For the win-ratio to become a prominent and reliable statistical method outside of cardiovascular disease, a straightforward approach to study design, particularly in terms of power and sample size determination, is needed. METHODS: Using an appropriate method for determining these metrics is vital to ensure the validity of the results obtained in a study. RESULTS: The WRestimates package provides easy-to-use functions that can be used for determining the required sample size and power of studies implementing the win-ratio. CONCLUSION: These methods enable the calculation of sample size and power based on estimands or pilot data, thereby eliminating the need for complex simulation-based methods that require numerous assumptions about the data.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

WREstimates: An R Package for Win-Ratio Sample Size and Power Calculations. — 科研速览 Science Skim