Curated packages for clinical programming — pharmaverse, stats, visualisation, and reporting.
ADaM in R Asset Library. Modular building blocks for ADaM dataset derivations following CDISC standards.
Export SAS XPT files from R with proper metadata, labels, and formats for CDISC submission.
Build complex, production-quality clinical tables using a declarative framework inspired by SAS PROC REPORT.
Shiny-based framework for exploratory clinical data analysis with modular, reusable app components.
Tables, Estimates and References for clinical trials — TLF generation using rtables.
Standardised storage of dataset metadata (variable-level specs) for clinical programming workflows.
The standard library for survival analysis: Kaplan-Meier, Cox PH, Weibull, and competing risks.
Mixed-effects models (MMRM-like) using maximum likelihood. Essential for repeated-measures clinical endpoints.
Estimated marginal means (LS-means) with contrasts and comparisons — post-hoc analysis after lme4 or lm.
Create Table 1 demographics / baseline characteristic tables with continuous + categorical variables.
The grammar of graphics for R. Publication-quality plots for clinical reports, posters, and CSRs.
A ggplot2-based API for Kaplan-Meier and cumulative incidence plots with risk tables and p-values.
Visualise correlation matrices as colour-coded plots — useful for biomarker and lab exploratory analysis.
The tidyverse grammar for data manipulation: filter, select, mutate, group_by, summarise.
Import Excel files (.xls, .xlsx) without Java or Perl dependencies — great for eCRF specs and metadata.
Produce reproducible reports in HTML, PDF, or Word from a single .Rmd file with R code and narrative.
Create clinical-grade RTF / Word tables with fine-grained formatting for CSR appendices.