Impact of Data Editing Methods on Estimates of Smoking Prevalence, Global Youth Tobacco Survey, 2007–2009

Accuracy of self-reported data may be improved by data editing, a mechanism to produce accurate information by excluding inconsistent data based on a set number of predetermined decision rules. We compared data editing methods in the Global Youth Tobacco Survey (GYTS) with other editing approaches and evaluated the effects of these on smoking prevalence estimates. We evaluated 5 approaches for handling inconsistent responses to questions regarding cigarette use: GYTS, do-nothing, gatekeeper, global, and preponderance. Compared with GYTS data edits, the do-nothing and gatekeeper approaches produced similar estimates, whereas the global approach resulted in lower estimates and the preponderance approach, higher estimates. Implications for researchers using GYTS include recognition of the survey’s data editing methods and documentation in their study methods to ensure cross-study comparability.