An Introduction to R Programming in Clinical Trials [Video]

Learn how R streamlines clinical trial planning, analysis, and reporting—so teams turn raw data into reproducible, inspection-ready evidence faster.

In this explainer, we show where R fits across the lifecycle: simulations and power before first patient in; scripted data checks and derivations during conduct; and analyses that include Kaplan–Meier survival curves, Cox proportional hazards, generalised linear models, and mixed-effects models for longitudinal data. You’ll hear how to produce safety summaries and exposure-adjusted incidence rates, and how to generate tables, listings, and figures in Word or PDF with reproducible code. We cover a practical workflow: build standardised analysis datasets aligned to CDISC ADaM, create a “reporting dataset” that mirrors the final table, render it with house styles, and export with consistent pagination and footnotes.

At Quanticate, our biometrics teams help sponsors design robust R workflows, deliver compliant TLFs, and maintain reproducible environments across studies. Submit an RFI today.