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Updated: Apr 19, 2026

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Reporting the reliability of accelerometer data with and without missing values.

Eric E Wickel1

  • 1Exercise and Sports Science, University of Tulsa, Tulsa, OK, United States of America.

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Reliability analysis using Generalizability theory revealed lower reliability for all observable accelerometer data (0.52-0.67) compared to complete data (0.74-0.87). This highlights the need to consider all participants for accurate group-level health outcome associations.

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Area of Science:

  • Physical Activity Measurement
  • Biostatistics
  • Child Development Research

Background:

  • Complete accelerometer data is often limited, potentially biasing reliability estimates.
  • Traditional reliability methods exclude participants with incomplete data, offering an incomplete view of sample characteristics.

Purpose of the Study:

  • To apply Generalizability theory to assess accelerometer data reliability for both complete and observable samples.
  • To characterize reliability across different ages and daily wear time criteria.

Main Methods:

  • Utilized accelerometer data from the Study of Early Child Care and Youth Development.
  • Performed missing value analyses and derived Generalizability coefficients from variance components.
  • Analyzed data stratified by age (9, 11, 12, 15 yrs) and wear time (6, 8, 10, 12 hrs).

Main Results:

  • Complete data reliability coefficients ranged from 0.74 to 0.87.
  • Observable data reliability coefficients were lower, ranging from 0.52 to 0.67.
  • Sample variability increased with longer wear time criteria and decreased with age.

Conclusions:

  • A reliability coefficient encompassing all participants, not just those with complete data, offers a more comprehensive perspective.
  • This global reliability measure can enhance understanding of group-level associations between physical activity and health outcomes.