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A case study in statistical software development for advanced evidence synthesis: the combined value of analysts and research software engineers

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posted on 2025-04-14, 13:42 authored by Naomi Bradbury, Thomas MorrisThomas Morris, Clareece NevillClareece Nevill, Janion Nevill, Ryan Field, Suzanne FreemanSuzanne Freeman, Nicola CooperNicola Cooper, Alexander SuttonAlexander Sutton

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.

Funding

SRP Complex Reviews Research Support Unit

National Institute for Health Research

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NIHR Leicester Biomedical Research Centre (BRC) and Applied Research Collaboration East Midlands (ARC EM)

History

Author affiliation

College of Life Sciences Population Health Sciences

Version

  • VoR (Version of Record)

Published in

BMC Medical Research Methodology

Volume

25

Issue

1

Pagination

13

Publisher

Springer Science and Business Media LLC

issn

1471-2288

eissn

1471-2288

Copyright date

2025

Available date

2025-04-14

Spatial coverage

England

Language

en

Deposited by

Mrs Clareece Nevill

Deposit date

2025-04-08

Data Access Statement

No datasets were generated or analysed during the current study.

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