First year of the Software Engineering working group - working together across organizations
Conference: ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop 2023
09/29/2023: 1:30 PM - 2:45 PM EDT
Parallel
The Software Engineering (SWE) Working Group (WG) was formed in August 2022 in the American Statistical Association (ASA) Biopharmaceutical Section (BIOP). The SWE WG facilitates cross-organizational collaboration with regular meetings, and currently includes more than 35 members from over 25 organizations. While most are from the pharmaceutical industry, the working group is open for academic and regulatory members too.
The primary goal of the SWE WG is to engineer R packages that implement important statistical methods to fill in gaps in the open-source statistical software landscape, focusing on the needs of biopharmaceutical applications. The first R package "mmrm" is setting a new standard for fitting mixed models for repeated measures (MMRM) in R.
The secondary goal is to develop and disseminate best practices for engineering high-quality open-source statistical software. The video series "Statistical Software Engineering 101" is introducing specific best practices in an accessible format. Furthermore the workshop "Good Software Engineering Practice for R Packages" has been successfully taught in person at a Basel Biometric Society seminar as well as a China R User Group workshop, and the materials are available publicly to train statisticians on best practices.
Communication is key, and the SWE WG was introduced in a BIOP report and maintains a website including a blog at https://rconsortium.github.io/asa-biop-swe-wg.
The SWE WG plans to develop additional new R packages, covering critical and innovative methodology topics in the health-technology assessment (HTA) space, covariate adjustment and Bayesian inference for MMRMs.
We describe the journey of the SWE WG so far and in particular the ingredients for working together successfully, including mutual interest, getting to know each other, and creating mutual trust.
Statistical Software
Open Source
Working Group
MMRM
Collaboration
R Packages
Presenting Author
Daniel Sabanes Bove, Roche
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