kaipingyang
Community@kaipingyang
R-based clinical data programming skills for CDISC SDTM mapping, ADaM derivation, and TFL reporting using the pharmaverse ecosystem.
Agent Skills by kaipingyang
Showing 13 vetted skills indexed across 1 GitHub repositories.
kaipingyangsdtm-oak
Generates R code deriving CDISC SDTM domains from raw EDC data using sdtm.oak.
kaipingyangtfl
Generates clinical TFL tables, figures, and listings code using tern and rtables from ADaM datasets.
kaipingyangadam-derive
Generates admiral-based R code templates for creating ADaM analysis datasets from SDTM inputs.
kaipingyangrun-shiny
Launches Shiny apps in Posit Workbench VS Code sessions with correct proxy URL configuration.
kaipingyangsdtm-map
Generates CDISC-compliant SDTM domain mapping R scripts using the sdtm.oak framework.
kaipingyangadmiral
Generates CDISC-conformant ADaM dataset derivation R code using the admiral pharmaverse package.
kaipingyanggithub-push
Push local commits to GitHub over SSH or HTTPS without exposing credentials.
kaipingyangadam
Query ADaM dataset structures and generate dummy ADaM test data in R.
kaipingyangsdtm
Answer SDTM structure questions and generate dummy SDTM domain data as R tibbles.
kaipingyangnew-user
Creates a student practice workspace by copying TODO-blanked CDISC starter scripts into a personal directory.
kaipingyangteal-clinical-modules
Build clinical trial TFL display apps with teal and teal.modules.clinical modules.
kaipingyangadmiral-bds
Generates R code deriving ADaM BDS datasets ADVS and ADLB from SDTM domains using admiral.
kaipingyangadmiral-adsl
Generates QC-ready R code deriving ADaM ADSL datasets from SDTM domains using admiral.
Frequently Asked Questions About kaipingyang
FAQPage SchemaWhat tasks can I accomplish with kaipingyang's clinical data skills?▼
You can generate R code for SDTM domain mapping from raw EDC data, derive ADaM datasets (ADSL, ADVS, ADLB) with admiral, produce TFL outputs like demographic tables and KM curves with tern/rtables, build teal clinical review apps, and create dummy SDTM/ADaM test data.
Who are these skills designed for?▼
Clinical statistical programmers, biostatisticians, and clinical data scientists working in GxP-compliant pharmaceutical environments who produce CDISC-compliant submission deliverables. A new-user skill also supports trainees learning SDTM/ADaM/TFL through guided TODO exercises.
What are the runtime prerequisites and dependencies?▼
Skills require R with sdtm.oak (>= 0.2.0), admiral, dplyr, tibble, lubridate, and pharmaversesdtm installed. SDTM derivation needs raw EDC/eCRF data plus a controlled terminology CSV; BDS derivation additionally requires a completed ADSL dataset and an ADaM specification.
Are these skills open source and what license applies?▼
Yes. The core derivation skills (sdtm-oak, admiral, admiral-adsl, admiral-bds) are released under the MIT license, authored by pharma-skills contributors and Navitas Data Sciences, and are free to use within the pharmaverse ecosystem.
How do the Shiny and GitHub utility skills fit in?▼
The run-shiny skill launches Shiny apps in Posit Workbench VS Code sessions with correct proxy URLs, while github-push handles pushing or pulling commits via SSH or HTTPS without exposing tokens, supporting day-to-day clinical programming project operations.