Data cleaning: longitudinal study cross-visit checks
Published in SAS Global Forum, March 23, 2014
Pubmed ID: 25383389
Abstract
Cross-visit checks are a vital part of data cleaning for longitudinal studies. The nature of longitudinal studies encourages repeatedly collecting the same information. Sometimes, these variables are expected to remain static, go away, increase, or decrease over time. This presentation reviews the naïve and the better approaches at handling one-variable and two-variable consistency checks. For a single-variable check, the better approach features the new ALLCOMB function, introduced in SAS® 9.2. For a two-variable check, the better approach uses a BY PROCESSING variable to flag inconsistencies. This paper will provide you the tools to enhance your longitudinal data cleaning process.
Funding Transparency
This work was possible through:
- Grant/Award
Additional details:
- Albert - NIH - U01AG033655 : Biomarkers of Cognitive Decline among Normal Individuals: the BIOCARD cohort
Entry last updated (DMY): 24-11-2024.