Data Cleaning and Preparation in R: Orientation
Learning Objectives
Learning Objectives
Learning Objectives
Explain the purpose of data cleaning and preparation in clinical research data management.
Distinguish between raw data, cleaned data, analysis-ready data, derived variables, and query outputs.
Describe a reproducible R workflow for importing REDCap exports and preparing datasets for review.
Explain the role of the REDCap API in automated data export and why API use must be governed carefully.
Identify and classify missing data using study-specific definitions and documentation.
Recode categorical variables transparently while preserving traceability to original values.
Create derived variables in R using protocol-defined rules.
Write cleaning scripts that are readable, rerunnable, and suitable for review by another data manager.
Produce simple cleaning logs and outputs that support query management, monitoring, and analysis preparation.