Quantifying sources of variability in gait analysis

Correcting lower limb segment axis misalignment in gait analysis: A simple geometrical method

“…Knee crosstalk was assessed by analysing the amplitude of knee adduction-abduction and the coefficient of determination (r²) between knee adduction-abduction and knee flexion-extension. Then, to assess the reproducibility of hip internal-external rotation, the inter-trial, inter-session and inter-subject standard deviations were investigated, in addition to the intersession-trial intraclass coefficient, following the statistical method proposed by Chia and Sangeux [21]. For the interpretation of the intraclass coefficient, the guidelines proposed by Koo and Lin [22] were used.…”

Editorial: Avoid being tripped up by statistics: Statistical guidance for a successful research paper

“…Apart from the direct knowledge of the extent of various sources of variability, such knowledge can be used to plan more efficient future studies or improve the assessments of patients so that meaningful changes in measurements can be detected. Chia and Sangeux [34] show how to estimate five sources of variability from gait analysis in their example and discuss how these variance components can be of clinical use. It is estimation of these variance components that should be central in reliability studies.…”

Test–retest reliability measures for curve data: an overview with recommendations and supplementary code

“…The CMC is very similar (and close to its maximum value of 1) for the first six scenarios in Table 2 (A1, A2, B1, B2, C1, C2). Several methodological shortcomings have been reported for the CMC (Chia & Sangeux, 2017;Sangeux, Passmore, Graham, & Tirosh, 2016). The method does not work for curves with a small ROM, since in such cases the term under the square root can be negative and CMC is undefined.…”