Which topic covers handling data gaps and unusual values in data?

Which topic covers handling data gaps and unusual values in data?

• A. Address data collection schedules
• B. Outline data management plan
• C. Handling missing values and outliers
• D. Describe adverse event coding

Answer: (C)

This topic focuses on data quality by addressing gaps and unusual values in the data. In clinical research, missing values and outliers can distort results if not handled properly, so predefined rules and methods are essential to preserve data integrity. You’d identify why data are missing (random vs. systematic), document it, and apply prespecified approaches such as imputation or analyses that accommodate missing data, along with clear procedures for verifying and handling outliers (checking for data entry errors, deciding whether to correct, transform, or exclude, and planning sensitivity analyses). This ensures the dataset remains reliable and the study conclusions are valid. The other topics cover when data are collected, the overall data management plan, or how adverse events are coded, but they don’t specifically address managing data gaps and unusual values.

This topic focuses on data quality by addressing gaps and unusual values in the data. In clinical research, missing values and outliers can distort results if not handled properly, so predefined rules and methods are essential to preserve data integrity. You’d identify why data are missing (random vs. systematic), document it, and apply prespecified approaches such as imputation or analyses that accommodate missing data, along with clear procedures for verifying and handling outliers (checking for data entry errors, deciding whether to correct, transform, or exclude, and planning sensitivity analyses). This ensures the dataset remains reliable and the study conclusions are valid. The other topics cover when data are collected, the overall data management plan, or how adverse events are coded, but they don’t specifically address managing data gaps and unusual values.