根据样本量、中位数、范围和/或四分位距估计样本均值和标准差
Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range
摘要：
在系统评价和荟萃分析中，研究者经常汇总一组相似临床试验的样本均值和标准差的结果。然而，一些试验使用中位数、最小值和最大值和/或第一和第三四分位数报告研究。因此，为了合并结果，可能必须估计这些试验的样本均值和标准差。在本文中，我们提出了改进现有的文献在几个方向。首先，我们证明了Hozo等人（2005）的样本标准差估计有一些严重的局限性，在实践中总是不太令人满意。受此启发，我们提出了一种新的估计方法，通过纳入样本量。其次，我们系统地研究了样本均值和标准差的估计问题，在更一般的设置，第一和第三四分位数也可用于试验。通过仿真研究，我们表明，所提出的方法大大改善了现有的方法，丰富了文献。我们总结了我们的工作与汇总表，作为一个全面的指导，在不同的情况下进行荟萃分析。
英文摘要：
In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al. (2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under more general settings where the first and third quartiles are also available for the trials. Through simulation studies, we demonstrate that the proposed methods greatly improve the existing methods and enrich the literature. We conclude our work with a summary table that serves as a comprehensive guidance for performing meta-analysis in different situations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
