Tackling Special Characters With SAS And R

By Eldho Alias, Principal Statistical Programmer; Vishal V Nair, Statistical Programmer III; Pooja Pradeep Pillai, Statistical Programmer II; and Hardik Sheth, Statistical Programming Technical Manager

In clinical research, data quality must be upheld at the highest level, yet hidden issues often lie beneath seemingly clean outputs. Non-printable and special characters — such as carriage returns, tabs, accented letters, or other non-ASCII symbols — can slip in at multiple points during data handling. These unseen elements can trigger problems like miscounts, unreadable reports, or formatting errors in final deliverables.

Because accuracy is directly tied to both patient safety and regulatory compliance, ignoring these anomalies can put the credibility of an entire study at risk. To help prevent this, Catalyst Clinical Research’s biostatistics team created a dual-language tool in SAS and R that efficiently scans for and cleans hidden characters across all study datasets. These issues frequently stem from manual entry, data transfers, file conversions, or automated scripts, making proactive detection and correction a necessity. If left unaddressed, special characters can distort analyses, mislead research teams, and slow down regulatory submissions, underscoring the importance of managing them effectively to ensure trustworthy results.

Take steps to safeguard your study outcomes by identifying and removing hidden characters early, protecting both data accuracy and compliance.