School of Medicine, Trinity College Dublin, Dublin, Ireland.
School of Physical Sciences, Dublin City University, Dublin, Ireland.
Elife. 2024 Jan 29;13:e93050. doi: 10.7554/eLife.93050.
In biomedical science, it is a reality that many published results do not withstand deeper investigation, and there is growing concern over a replicability crisis in science. Recently, Ellipse of Insignificance (EOI) analysis was introduced as a tool to allow researchers to gauge the robustness of reported results in dichotomous outcome design trials, giving precise deterministic values for the degree of miscoding between events and non-events tolerable simultaneously in both control and experimental arms (Grimes, 2022). While this is useful for situations where potential miscoding might transpire, it does not account for situations where apparently significant findings might result from accidental or deliberate data redaction in either the control or experimental arms of an experiment, or from missing data or systematic redaction. To address these scenarios, we introduce Region of Attainable Redaction (ROAR), a tool that extends EOI analysis to account for situations of potential data redaction. This produces a bounded cubic curve rather than an ellipse, and we outline how this can be used to identify potential redaction through an approach analogous to EOI. Applications are illustrated, and source code, including a web-based implementation that performs EOI and ROAR analysis in tandem for dichotomous outcome trials is provided.
在生物医学科学中，许多已发表的研究结果经不住更深入的调查，人们对科学领域的可重复性危机越来越关注。最近，引入了无意义椭圆（Ellipse of Insignificance，EOI）分析作为一种工具，使研究人员能够评估二分类结局设计试验中报告结果的稳健性，为同时容忍对照和实验臂中事件和非事件之间编码错误的程度提供精确的确定性值（Grimes，2022）。虽然这对于可能发生潜在编码错误的情况很有用，但它并未考虑到在实验的对照或实验臂中，由于偶然或故意的数据删失，或者由于缺失数据或系统删失，可能导致明显显著发现的情况。为了解决这些情况，我们引入了可达到删失区域（Region of Attainable Redaction，ROAR），这是一种扩展 EOI 分析以考虑潜在数据删失情况的工具。它生成一个有界的立方曲线，而不是椭圆，我们概述了如何通过类似于 EOI 的方法，使用这种方法来识别潜在的删失。本文说明了应用案例，并提供了包括用于二分类结局试验的 EOI 和 ROAR 分析的基于网络的实现的源代码。
