医学
排名(信息检索)
背景(考古学)
序数数据
可能性
序数回归
结果(博弈论)
统计能力
优势比
梅德林
荟萃分析
家庭医学
联想(心理学)
范畴变量
概念框架
研究设计
数据科学
数据挖掘
度量(数据仓库)
统计模型
作者
Chris J. Selman,Sean W. X. Ong,Melissa Middleton,Leon Di Stefano,Elyssia Bourke,Elliot Long,Franz E Babl,K. J. Lee
标识
DOI:10.1111/1742-6723.70201
摘要
ABSTRACT Ordinal outcomes are becoming increasingly common in clinical research because they can incorporate multiple clinical states into a single outcome, offer increased statistical power compared to binary outcomes, and can be applied across a range of illness severities. However, ordinal outcomes may be unfamiliar to many clinicians and researchers. In this paper, we aim to provide a practical conceptual overview of ordinal outcomes in the context of emergency medicine, discuss their pros and cons, and describe the associated effect measures and statistical methods that can be used to estimate them. We describe the different types of ordinal outcomes, including hierarchical composite endpoints (e.g., Desirability of Outcome Ranking or DOOR); outline the target parameters that may be of interest, such as the common odds ratio and win ratio; and describe the statistical methods for estimating these parameters, including their assumptions and limitations. Ordinal outcomes offer a flexible, efficient, and nuanced way to measure treatment effects but require careful planning for how treatment effects will be estimated and communicated. We hope this review will make these outcomes more accessible for clinical researchers.
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