In the social and medical sciences, researchers often use meta-analysis to aggregate findings from several studies. However, conducting a meta-analysis is a time consuming enterprise, that requires not just domain specific knowledge and analytical experience, but considerable data management skills as well. To aid reproducible research, it should be possible to handle tasks - from collecting to analyzing data - directly in R. Even though there are several useful packages to conduct the statistical part of a meta-analysis, there is a lack of packages that deal with the data management tasks that are typically needed. To fill this gap, we created the {metamanager} package. The package provides several functions for conducting reproducible meta-analysis, while the code remains human readable. Key functionality involves merging and tidying article meta-data, flagging duplicates, creating files for human coding, assessing coding performance, detecting and correcting human errors, etc. The package has functions to manage spreadsheets through Google Drive, providing a front-end for manual data entry, access management, version control, and collaborative editing.
https://github.com/nthun/metamanager