Statistical Software
Overview
I develop open-source statistical software to facilitate the application of advanced statistical methods and promote reproducible research. My goal is to bridge methodological research and practical implementation by providing accessible tools for researchers and practitioners.
Most of my software is developed in R and released as open-source, accompanied by documentation, examples and scientific publications.
Current Software
CompAREdesign
An R package for designing randomized clinical trials with composite endpoints, allowing researchers to evaluate alternative trial designs under different assumptions and scenarios.
MSMpred
An R package for developing and evaluating prediction models in multiple sclerosis research, with a focus on reproducibility and transparent methodology.
Other Developments
Beyond R packages, I also develop:
- Shiny applications for interactive statistical analyses.
- Reproducible workflows using Quarto and R Markdown.
- Simulation tools for methodological research.
- Open educational resources for statistics.
Philosophy
I believe that statistical methods should be accompanied by high-quality, open and reproducible software. Making research methods accessible through well-documented software is an essential part of improving scientific practice.
