Longitudinal analysis reveals missing data causes in wearable devices, suggesting improvements for data accuracy.
Evidence of missingness in this dataset was consistent with MAR. Potential causes of missingness include device removal, battery failure, and technical malfunctions. These findings have important implications for both wearable device users and future research. Understanding the mechanisms behind missingness can inform strategies to improve data quality, particularly in low-resource settings, and allow researchers to manage missingness using appropriate strategies designed to handle MAR data without introducing bias into the results.
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Mobley et al. (2026) studied this question.
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