The process of data standardization typically involves several steps:
Data Cleaning: Removing errors, duplicates, and inconsistencies from the dataset. Data Transformation: Converting data into a common format or unit of measure. For example, converting heights from feet and inches to centimeters. Variable Standardization: Ensuring that variables are defined and measured consistently across different datasets. This might involve harmonizing definitions of health outcomes or exposure factors. Coding and Classification: Using standardized codes and classifications, such as the International Classification of Diseases (ICD) for health conditions.
