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    Measurement strategy and statistical power in studies assessing gait stability and variability in older adults

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    Authors
    Toebes, M.
    Hoozemans, M.
    Mathiassen, Svend
    Dekker, J.
    van Dieën, J.
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Toebes, M. and Hoozemans, M. and Mathiassen, S. and Dekker, J. and van Dieën, J. 2016. Measurement strategy and statistical power in studies assessing gait stability and variability in older adults. Aging Clinical and Experimental Research. 28 (2): pp. 257-265.
    Source Title
    Aging Clinical and Experimental Research
    DOI
    10.1007/s40520-015-0390-8
    ISSN
    1594-0667
    School
    School of Physiotherapy and Exercise Science
    URI
    http://hdl.handle.net/20.500.11937/68453
    Collection
    • Curtin Research Publications
    Abstract

    © 2015, The Author(s). Background: Gait variability and stability measures might be useful to assess gait quality changes after fall prevention programs. However, reliability of these measures appears limited. Aims: The objective of the present study was to assess the effects of measurement strategy in terms of numbers of subjects, measurement days and measurements per day on the power to detect relevant changes in gait variability and stability between conditions among healthy elderly. Methods: Sixteen healthy older participants [65.6 (SD 5.9) years], performed two walking trials on each of 2 days. Required numbers of subjects to obtain sufficient statistical power for comparisons between conditions within subjects (paired, repeated-measures designs) were calculated (with confidence intervals) for several gait measures and for different numbers of trials per day and for different numbers of measurement days. Results: The numbers of subjects required to obtain sufficient statistical power in studies collecting data from one trial on 1 day in each of the two compared conditions ranged from 7 to 13 for large differences but highly correlated data between conditions, up to 78–192 for data with a small effect and low correlation. Discussion: Low correlations between gait parameters in different conditions can be assumed and relatively small effects appear clinically meaningful. This implies that large numbers of subjects are generally needed. Conclusion: This study provides the analysis tools and underlying data for power analyses in studies using gait parameters as an outcome of interventions aiming to reduce fall risk.

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