Gait variability and stability measures might be useful to assess gait quality changes after fall prevention programs. However, reliability of these measures appears limited. 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. 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. 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. 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. 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.