R packages:

• CompARE: Sample size and effect size calculation for composite endpoints. [GitHub] [CRAN] [website] [Shiny-app]

• NCC: Design and analysis of platform trials with non-concurrent controls. (Maintainer: Pavla Krotka). [GitHub] [CRAN] [website] [Slides]

• 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] [CRAN]

• Survbin: Two-sample statistics for binary and time-to-event outcomes. [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] [Shiny-app]

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]

Talks:

Slides on Model-based time trend adjustments in platform trials with non-concurrent controls is available on Zenodo.

Slides on Adaptive selection of composite endpoints and sample size reassessment based on blinded data is available on Zenodo.

Thesis:

My thesis dissertation is available on Zenodo.

Dissemination:

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

Outreach:

Video on survival analysis. See Youtube channel Llampecs de Ciència.

Poster on multi-state models for Science Week 2020. [Zenodo]