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Direct linkHannah R. Thompson; Joni Ladawn Ricks-Oddie; Margaret Schneider; Sophia Day; Kira Argenio; Kevin Konty; Shlomit Radom-Aizik; Yawen Guo; Dan M. Cooper – Journal of School Health, 2025
Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…
Descriptors: Physical Fitness, Data Interpretation, Statistical Bias, Youth
