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报告题目:Detecting the skewness of data from the sample size and the five-number summary


报告摘要:For clinical studies with continuous outcomes, when the data are potentially skewed, researchers may choose to report the whole or part of the five-number summary (the sample median, the first and third quartiles, and the minimum and maximum values), rather than the sample mean and standard deviation. For the studies with skewed data, if we include them in the classical meta-analysis for normal data, it may yield misleading or even wrong conclusions. In this paper, we develop a flow chart and three new tests for detecting the skewness of data from the sample size and the five-number summary. Simulation studies demonstrate that our new tests are able to control the type I error rates, and meanwhile provide good statistical power. A real data example is also analyzed to demonstrate the usefulness of the skewness tests in meta-analysis and evidence-based practice.


报告地点:腾讯会议  ID号: 392429809


报告人简介:石建栋,在香港浸会大学数学系攻读博士学位,师从童铁军教授。2015年于山东大学数学学院取得学士学位;2018年于山东大学数学学院取得硕士学位,师从林路教授。主要研究方向为meta分析及医学统计。目前两篇文章分别发表于Research Synthesis Methods (影响因子5.299) 和Statistics and Its Interface。