trialdiff - Clinical Trial Data-Cut Change Detection and Impact Assessment
A transparent, rule-based framework for detecting changes
between successive data cuts of clinical trial datasets,
classifying those changes into clinically meaningful
categories, tracing user-defined data lineage, and assessing
which downstream analyses and outputs may be affected. The
package is designed to complement existing low-level data frame
comparison tools by adding clinical-trial-specific
classification, lineage and impact-assessment layers on top of
deterministic comparison. The rule-based classification is
similar in spirit to the data validation infrastructure of van
der Loo and de Jonge (2021) <doi:10.18637/jss.v097.i10>.
