title: Measurement strategy and statistical power in studies assessing gait stability and variability in older adults.
abstract: 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.
  
  
  OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: MOVE Research Institute Amsterdam, Faculty of Human Movement Sciences, VU University Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands.
authors.forename: Marcel J P
authors.initials: MJ
authors.lastname: Toebes
authors.affiliation: MOVE Research Institute Amsterdam, Faculty of Human Movement Sciences, VU University Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands.
authors.forename: Marco J M
authors.initials: MJ
authors.lastname: Hoozemans
authors.affiliation: Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, Gävle, Sweden.
authors.forename: Svend Erik
authors.initials: SE
authors.lastname: Mathiassen
authors.affiliation: Department of Rehabilitation Medicine, VU University Medical Center, EMGO Institute for Health and Care Research, Amsterdam, The Netherlands.
authors.forename: Joost
authors.initials: J
authors.lastname: Dekker
authors.affiliation: MOVE Research Institute Amsterdam, Faculty of Human Movement Sciences, VU University Amsterdam, Van der Boechorststraat 7-9, 1081BT, Amsterdam, The Netherlands. j.van.dieen@vu.nl.
authors.forename: Jaap H
authors.identifier: http://orcid.org/0000-0002-7719-5585
authors.initials: JH
authors.lastname: van Dieën
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D003627:Data Interpretation, Statistical; D005260:Female; D005684:Gait; D015577:Geriatric Assessment / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D017063:Outcome Assessment, Health Care; D015203:Reproducibility of Results; D016138:Walking
keywords: Between-day variance; Gait variability; Local dynamic stability; Measurement design; Walking; Within-day variance