Reproducing Epidemiologic Research and Ensuring Transparency

Abstract

Measures for ensuring that epidemiologic studies are reproducible include making data sets and software available to other researchers so they can verify published findings, conduct alternative analyses of the data, and check for statistical errors or programming errors. Recent developments related to the reproducibility and transparency of epidemiologic studies include the creation of a global platform for sharing data from clinical trials and the anticipated future extension of the global platform to non–clinical trial data. Government agencies and departments such as the US Department of Veterans Affairs Cooperative Studies Program have also enhanced their data repositories and data sharing resources. The Institute of Medicine and the International Committee of Medical Journal Editors released guidance on sharing clinical trial data. The US National Institutes of Health has updated their data-sharing policies. In this issue of the Journal, Shepherd et al. (Am J Epidemiol. 2017;186:387–392) outline a pragmatic approach for reproducible research with sensitive data for studies for which data cannot be shared because of legal or ethical restrictions. Their proposed quasi-reproducible approach facilitates the dissemination of statistical methods and codes to independent researchers. Both reproducibility and quasi-reproducibility can increase transparency for critical evaluation, further dissemination of study methods, and expedite the exchange of ideas among researchers.

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