Researches |

Sports Analytics

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Sports analytics combines statistical methodology, machine learning and data science to support evidence-based decision making in sport.

My research focuses on:

Performance analysis
Injury prevention
Survival analysis in sport
Prediction models
Reproducible research

Current topics

Statistical methodology for sports science
Reporting quality in sports analytics
Meta-research
European research collaborations

Biostatistics

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Biostatistics provides the methodological foundation for evidence-based biomedical research. My work focuses on the development and application of statistical methods that improve the design, analysis and reporting of clinical and observational studies.

My research combines methodological developments with practical applications in collaboration with clinicians, epidemiologists and biomedical researchers.

Research Interests

Clinical trials
Survival analysis
Generalized linear models
Composite endpoints
Prognostic and prediction models
Meta-research and reporting quality

Software

I actively develop open-source software in R to facilitate the implementation of statistical methods and promote reproducible research. My work includes packages for clinical trial design, prediction models and methodological research.

Collaborations

I collaborate with multidisciplinary teams from universities, hospitals and research institutes, contributing statistical expertise to biomedical and translational research projects.

Clinical Trials

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Randomized clinical trials are the gold standard for evaluating the efficacy and safety of healthcare interventions. My research focuses on the development and application of statistical methods that improve trial design, analysis and reporting, contributing to more reliable and reproducible clinical research.

I am particularly interested in methodological challenges that arise in modern clinical trials and in translating statistical advances into practical tools for researchers.

Research Interests

Design of randomized clinical trials
Composite endpoints
Survival analysis
Sample size determination
Statistical simulation
Reporting guidelines for clinical research

Methodological Research

A major part of my work involves developing and evaluating statistical methods through simulation studies and applying them to real biomedical research. This includes the design of innovative approaches for complex trial settings and the assessment of their statistical performance.

Software

To facilitate the application of these methods, I develop open-source R packages that allow researchers to design studies, evaluate statistical methods and reproduce published analyses.

Collaboration

I collaborate with clinicians, epidemiologists and biomedical researchers in multidisciplinary projects, providing statistical expertise from study design to the interpretation and communication of results.

Research Methodology

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Research methodology is a central component of my work. I investigate how statistical methods are applied, reported and interpreted, with the aim of improving the quality, transparency and reproducibility of scientific research.

My research combines methodological developments with meta-research studies that evaluate current research practices and identify opportunities to improve statistical reporting and study design.

Research Interests

Reporting guidelines
Meta-research
Reproducible research
Statistical reporting
Study design and methodology
Research quality assessment

Current Research

A major focus of my recent work is the evaluation of statistical reporting in biomedical and sports science research. By systematically assessing published studies, I aim to identify common methodological limitations and promote best practices for transparent and reproducible research.

I am also interested in developing practical recommendations and methodological tools that help researchers design, analyse and report studies more effectively.

Impact

Improving research methodology ultimately contributes to more reliable scientific evidence, better decision-making and greater confidence in research findings. My goal is to bridge methodological research with practical guidance that supports researchers across different scientific disciplines.

Statistical Software

Mon, 01 Jan 0001 00:00:00 +0000

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.