相对风险和几率比率的置信区间可以预测在元分析中不能满足最佳信息大小的情况

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An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

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M Hassan Murad1, George A Tomlinson2, Romina Brignardello-Petersen3

  • 1Evidence-based Practice Center, Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA.

Journal of clinical epidemiology
|December 26, 2024
PubMed
概括

信任区间比率在元分析中有效排除了最佳信息大小 (OIS),但不能证实它. 这有助于因不准确性而降低证据确定性,特别是当可信的效应大小超过30%的相对风险降低时.

关键词:
确定性 确定性 确定性品位等级 品位等级 品位等级不准确性 不准确性进行元分析分析.最佳的信息大小是什么?动力 动力 动力 动力

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