The epidemiology of errors in data capture, management, and analysis: A scoping review of retracted articles and retraction notices in clinical and translational research.

Introduction: To better understand and prevent research errors, we conducted a first-of-its-kind scoping review of clinical and translational research articles that were retracted because of problems in data capture, management, and/or analysis.

Methods: The scoping review followed a preregistered protocol and used retraction notices from the Retraction Watch Database in relevant subject areas, excluding gross misconduct. Abstracts of original articles published between January 1, 2011 and January 31, 2020 were reviewed to determine if articles were related to clinical and translational research.

Facilitating reproducible research through direct connection of data analysis with manuscript preparation: StatTag for connecting statistical software to Microsoft Word.

Objectives: To enhance reproducible research by creating a broadly accessible, free, open-source software tool for connecting Microsoft Word to statistical programs (R/R Markdown, Python, SAS, Stata) so that results may be automatically updated in a manuscript.

Materials And Methods: We developed StatTag for Windows as a Microsoft Word plug-in using C# and for macOS as a native application using Objective-C. Source code is available under the MIT license at https://github.