| 张盛婕,王杨,李卫.临界点分析法在处理临床研究缺失数据中的应用[J].Chinese journal of Epidemiology,2017,38(5):674-678 |
| 临界点分析法在处理临床研究缺失数据中的应用 |
| Application of tipping-point analysis to address missing data in clinical studies |
| Received:October 13, 2016 |
| DOI：10.3760/cma.j.issn.0254-6450.2017.05.024 |
| KeyWord: 临界点分析法 临床研究 缺失数据 |
| English Key Word: Tipping-point analysis Clinical study Missing data |
| FundProject:北京协和医学院青年基金暨中央高校基本科研业务费专项（3332015071） |
| Author Name | Affiliation | E-mail | | Zhang Shengjie | Medical Research and Biometrics Center, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102300, China | | | Wang Yang | Medical Research and Biometrics Center, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102300, China | | | Li Wei | Medical Research and Biometrics Center, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 102300, China | liwei@mrbc-nccd.com |
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| Abstract: |
| 为应用可视化的临界点分析法处理临床研究缺失数据并探讨相关问题。枚举因缺失值导致的“所有”可能结局，并找出组间比较P值发生变化（P=0.05为差异有统计学意义）的临界点，进一步计算P<0.05的组合所占比例，判定研究结论的可靠性。临界点分析法可用于连续型或二分类结局的临床研究数据，并找到对应的临界点。在连续型结局实例中P<0.05区域的比例为93.6%，否定零假设即试验成功的可靠性较高；二分类结局实例P<0.05区域的比例为29.7%，否定零假设即试验成功的可靠性较低。临界点分析法可用于含缺失数据的临床研究，为结果判定提供可视化的判定依据。 |
| English Abstract: |
| To use a visualized method, tipping-point analysis to address missing data in clinical study and discuss related problems. All the possible outcomes caused by missing data were listed and the tipping points where P-values of hypothesis test changed at 0.05 significant level were found out, then the ratio of P<0.05 was calculated, reflecting the reliability of the study's result. Tipping-point analysis can be applied to both continuous and binary data to help find points where p-values are changed. The area of P<0.05 of continuous data is 93.6%, indicating that the reliability of success of the study is large; and the area of P<0.05 of binary data is 29.7%, reflecting that the reliability of success of the study is small. Tipping-point analysis, which provides a visualized evidence for decision making, is suitable for analyzing clinical studies with missing data. |
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