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A case study in statistical software development for advanced evidence synthesis: the combined value of analysts and
Naomi Bradbury1, Tom Morris2,3, Clareece Nevill2,3
1Biostatistics Research Group, Department of Population Health Sciences, University of Leicester, Leicester, UK. nvm4@leicester.ac.uk.
Background:
Since 2015, the Complex Reviews Synthesis Unit (CRSU) has developed a suite of web-based applications (apps) that conduct complex evidence synthesis meta-analyses through point-and-click interfaces. This has been achieved in the R programming language by combining existing R packages that conduct meta-analysis with the shiny web-application package. The CRSU apps have evolved from two short-term student projects into a suite of eight apps that are used for more than 3,000 h per month.
Aim:
Here, we present our experience of developing production grade web-apps from the point-of-view of individuals trained primarily as statisticians rather than software developers in the hopes of encouraging and inspiring other groups to develop valuable open-source statistical software whilst also learning from our experiences.
Key Challenges:
We discuss how we have addressed challenges to research software development such as responding to feedback from our real-world users to improve the CRSU apps, the implementation of software engineering principles into our app development process and gaining recognition for non-traditional research work within the academic environment.
Future Developments:
The CRSU continues to seek funding opportunities both to maintain and further develop our shiny apps. We aim to increase our user base by implementing new features within the apps and building links with other groups developing complementary evidence synthesis tools.
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