ABCMETAapp：R Shiny应用程序，用于通过近似贝叶斯计算估计荟萃分析的平均值和标准差（ABC）
ABCMETAapp: R Shiny Application for Simulation-based Estimation of Mean and Standard Deviation for Meta-analysis via Approximate Bayesian Computation (ABC)
摘要：
背景和目的：在基于连续结局的荟萃分析中，所选研究的估计平均值和相应的标准差是获得平均值及其置信区间汇总估计值的关键输入。我们经常遇到文献中没有直接报道这些量的情况。相反，报告了其他汇总统计量，如中位数、最小值、最大值、四分位数和研究样本量。基于可用的汇总统计量，我们需要估计荟萃分析的平均值和标准差。方法：我们开发了一个基于近似贝叶斯计算（ABC）的R Shiny代码，ABCMETA，来处理这种情况。结果：在这篇文章中，我们提出了一个交互式和用户友好的R Shiny应用程序来实现所提出的方法（名为ABCMETAapp）。在ABCMETAapp中，当结果变量的分布是偏态或重尾时，用户可以选择正态分布以外的基础结果分布。我们将通过示例展示如何运行ABCMETAapp。结论：ABCMETAapp提供了一个R Shiny实现。这种方法比现有的分析方法更灵活，因为估计可以基于结果变量的五种不同分布（正态分布、对数正态分布、指数分布、Weibull分布和Beta分布）。
英文摘要：
Background and Objective: In meta-analysis based on continuous outcome, estimated means and corresponding standard deviations from the selected studies are key inputs to obtain a pooled estimate of the mean and its confidence interval. We often encounter the situation that these quantities are not directly reported in the literatures. Instead, other summary statistics are reported such as median, minimum, maximum, quartiles, and study sample size. Based on available summary statistics, we need to estimate estimates of mean and standard deviation for meta-analysis. Methods: We developed a R Shiny code based on approximate Bayesian computation (ABC), ABCMETA, to deal with this situation. Results: In this article, we present an interactive and user-friendly R Shiny application for implementing the proposed method (named ABCMETAapp). In ABCMETAapp, users can choose an underlying outcome distribution other than the normal distribution when the distribution of the outcome variable is skewed or heavy tailed. We show how to run ABCMETAapp with examples. Conclusions: ABCMETAapp provides a R Shiny implementation. This method is more flexible than the existing analytical methods since estimation can be based on five different distribution (Normal, Lognormal, Exponential, Weibull, and Beta) for the outcome variable.
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。
