CAMIS Awards 2025
Reflections on key contributors for 2025 and looking ahead to 2026!
The CAMIS team look forward to another year of collaboration and growth, and also reflect on the achievements of the previous 12 months.
For the end of 2025, the CAMIS leadership team of Christina, Yannick and Lyn extended thanks for all of the community's ongoing contributions and support to the project. Additionally, there were some special awards announced for people who have really impacted the project during 2025, helping CAMIS to continue to grow and improve:
For Technical Innovation: Michael Walshe - Thank you for adding Caching to the website to make it run so much faster!
For Shaping our Future: Logan Johnson - Thank you for challenging our core roots to be better - updates to the table of contents, help pages, running SAS and parallelisation.
For Communications: Molly MacDiarmid - Thank you for organizing all of our wonderful blogs this year.
For Student of the Year: Sarah Brosens - Thank you for your amazing work on tipping point and recurrent event analysis.
For Newcomer of the Year: Miriam Amor - Thank you for your amazing work on generalised estimating equations and presenting at PHUSE.
For Best Editor: Abi Terry - Thank you for correcting and expanding our previous work on Cox proportional hazards tie-handling.
For Stretching Boundaries: Fedor Logvin - Thank you for adding great sections on propensity score matching and weighting.
For Being an All Star Contributor : Chi-Rong Li - Thank you for completing R, SAS, EAST & Comparison pages on group sequential design for survival sample size.
___
CAMIS (Comparing Analysis Method Implementations in Software) is a PHUSE DVOST working group (WG) collaboration with PSI AIMS SIG. The CAMIS open-source repository aims to provide essential information about the application of statistical methodology in various software (including SAS, R and Python). A lack of clear specification of methods can result in an inability to reproduce the same results in different software, especially as not all options are available in all software, and existing documentation can sometimes be unclear.
By documenting found differences in a repository, we aim to reduce time-consuming efforts within the community, where multiple people are investigating the same issues. Please help us in 2026 and beyond to build a high quality, easy-to-read and comprehensive repository. With your support, the repository will continue to grow in content and be a vital source for medical statisticians and programmers. Explore the website repository (CAMIS - A PHUSE DVOST Working Group) and check how to Get Involved.