Welcome!
I am a postdoctoral researcher at the Center for Medical Data Science. My research focuses on methods and software for clinical trials with multiple endpoints and adaptive platform trials.
- Clinical trials
- Adaptive designs
- Survival analysis
- Platform trials
-
PhD in Statistics and Operations Research, 2020
Universitat Politècnica de Catalunya
-
MSc in Statistics and Operations Research, 2016
Universitat Politècnica de Catalunya and Universitat de Barcelona
-
BSc in Mathematics, 2014
Universitat de Barcelona
Recent Publications
Software
R packages & Shiny apps
R packages:
-
CompARE: Sample size and effect size calculation for composite endpoints. [GitHub] [CRAN] [website] [Shiny-app]
-
Survbin: Two-sample statistics for binary and time-to-event outcomes. [GitHub] [website]
-
survmixer: Design of clinical trials with survival endpoints based on binary response. [GitHub] [CRAN] [website]
-
eselect: R package for adaptive trial designs with endpoint selection and sample size reassessment. [GitHub]
-
NCC: Design and analysis of platform trials with non-concurrent controls. (Maintainer: Pavla Krotka). [GitHub] [website]
Repositories:
-
Non-concurrent controls: Model-based time trend adjustments in platform trials with non-concurrent controls. [GitHub]
-
Optimal allocations: Optimal allocation in platform trials. [GitHub]
Fun stuff:
- pum! (together with Pol Castellano and Guillermo Villacampa): Shiny app to explore Florence Nightingale’s data in Crimean War. [GitHub] [Shiny-app] [YouTube-Tutorial]
Materials
in Open Access
Talks:
Slides on Model-based time trend adjustments in platform trials with non-concurrent controls is available on Zenodo.
Thesis:
My thesis dissertation is available on Zenodo.
Outreach:
Poster on multi-state models for Science Week 2020. [Zenodo]
Video on survival analysis. See Youtube channel Llampecs de Ciència.
Tweetorial on the Shiny-app CompARE by Jordi Cortés
Tweetorial on Model-based time trend adjustments in platform trials with non-concurrent controls by Kert Viele
