Adverse Event Tables: SOC and PT Reporting
A practical guide to constructing and interpreting adverse event tables by System Organ Class and Preferred Term, including subject-level counting, treatment-emergent events, severity, seriousness, relatedness, MedDRA hierarchy, and QC.
Adaptive Randomization Methods
A computational guide to adaptive randomization methods in clinical trials, including response-adaptive randomization, covariate-adaptive randomization, minimization, play-the-winner designs, Bayesian adaptive randomization, operating characteristics, type I error, power, allocation ratios, and implementation considerations.
gtsummary Package for Clinical Tables
A practical guide to the gtsummary R package for clinical trial tables, including baseline characteristics, descriptive statistics, p-values, regression tables, survival summaries, formatting, customization, reporting workflows, and validation.
ggplot2 for Clinical Trial Visualizations
A practical guide to using ggplot2 for clinical trial visualizations, including longitudinal laboratory plots, adverse event charts, boxplots, spaghetti plots, forest plots, Kaplan-Meier displays, treatment comparisons, clinical reporting standards, and R implementation.
eCTD and Electronic Submission Requirements
A practical guide to eCTD and electronic regulatory submission requirements, including CTD modules, eCTD architecture, sequences, lifecycle management, XML backbones, PDF requirements, hyperlinks, bookmarks, validation, FDA requirements, eCTD v4.0, EU requirements, submission gateways, and regulatory submission QC.
admiralonco Part 2: Advanced Oncology ADaM Programming
An advanced practical guide to oncology ADaM programming with admiralonco, covering ADRS, ADTR, ADTTE, response criteria, confirmation logic, event derivation, reusable programming patterns, validation, and production-quality R workflows.
admiral R Package: Getting Started
An advanced guide to the admiral R package for statistical programmers, covering ADSL, BDS, OCCDS, joins, baseline, change, computed parameters, treatment-emergent flags, reusable derivations, testing, traceability, and QC.
Writing Reusable R Functions for TLF Generation
A practical guide to writing reusable R functions for clinical trial Tables, Listings, and Figures (TLFs), including function design, arguments, validation, formatting, parameterization, debugging, testing, and production-ready reporting workflows.
Version Control with Git for Biostatisticians
A practical guide to using Git version control in clinical biostatistics, including repositories, commits, branches, merges, pull requests, code review, R and RStudio workflows, TLF development, reproducibility, renv, .gitignore, merge conflicts, tagging, and regulatory considerations.
Validating SAS Programs in Regulated Environments
A practical guide to validating SAS programs in regulated clinical research environments, including validation planning, risk assessment, independent programming, QC, test cases, traceability, change control, audit trails, documentation, and inspection readiness.