ABCMETAapp: R shiny application for simulation-based estimation of mean and standard deviation for meta-analysis via approximate Bayesian computation.

ABSTRACT: 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. We developed an R Shiny code based on approximate Bayesian computation (ABC), ABCMETA, to deal with this situation. In this article, we present an interactive and user-friendly R Shiny application for implementing the proposed method (named ABCMETAapp). I

SUBMITTER: Kwon D 

PROVIDER: S-EPMC8596912 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature