Self-learning software tools for data analysis in meta-analysis

cisions [1]. Hence, researchers need additional knowledge regarding software programs used to perform meta-analysis. In the published literature of high-impact-factor anesthesia journals, we observed that RevMan 5 (Review Manager [RevMan], [Computer program],Version 5.4, The Cochrane Collaboration, 2020) is the most frequently used primary meta-analytical software package. However, detailed information on additional auxiliary software use is inadequate. The challenge arises when multiple analyses are required, and the researcher needs to choose the correct software program. Apart from primary statistical software programs, such as SAS (Copyright SAS Institute Inc., SAS Campus Drive, USA), R (R Core Team [2017], R: A language and environment for statistical computing. R Foundation for Statistical Computing, Austria. Available from https:// www.R-project.org/), STATA (StataCorp., 2015. Stata Statistical Software: Release 14. StataCorp LP), SPSS (IBM Corp. IBM SPSS Statistics for Windows [Internet], IBM Corp., 2017. Available from https://hadoop.apache.org) and Cochrane RevMan calculators (https://training.cochrane.org/resource/revman-calculator), one should be aware of user-friendly auxiliary software to progress in meta-analysis. This is because primary software programs are deficient in performing additional analyses, such as meta-regressions and network plotting. Generally, it is believed that clinical researchers often make mistakes when they undertake their own data analysis by not enlisting a statistician before and after undertaking a study. Contrariwise, it is also true that self-learning of additional software by a researcher critically reduces the need for collaborating with a statistician, which in turn might improve the quality of research. In subsequent paragraphs, we report the types and representative examples of software used for data management in meta-analysis. For data extraction from images, authors can use Engauge digitizer (https://markummitchell.github.io/engauge-digitizer/) effectively and reliably to import images from an article directly or via Microsoft Paint. Using axis point and curve point tools, one can define the graph axis and data set points of an imported image, respectively. The numerical data obtained are exported and saved as . CSV files. Other software packages that have similar functions include WebPlotDigitizer (https://automeris.io/WebPlotDigitizer/) or Plot Digitizer (https://sourceforge.net/projects/plotdigitizer/files/). OriginPro (https:// www.originlab.com/) is beneficial to obtain the data from complex formats, such as 2D-image or embedded matrix sheets. Although RevMan 5 can be used for sensitivity analysis, meta-regression requires a different software. The funnel plot asymmetry evaluation and derivation of Egger or Omnibus P values can be easily derived using JASP (https://jasp-stats.org/ 2017/11/15/meta-analysis-jasp/). The . CSV data file specifically containing study name, estimate, and standard error (SE) are exported from RevMan. Nevertheless, meta-regression factors/covariates should be entered for each study. CoeffiReceived: February 21, 2021 Revised: March 4, 2021 Accepted: March 7, 2021