2022
DOI: 10.1007/s11634-022-00500-y
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Basis expansion approaches for functional analysis of variance with repeated measures

Abstract: The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the aim consists of detecting differences in gait patterns when several independent samples of subjects walk or run under different conditions (repeated measures). Classic kinematic studies often analyse discrete summaries of the sample curves discarding important info… Show more

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Cited by 8 publications
(2 citation statements)
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“…In this manner, different curves with the same V set and V reset lead to a non-negligible variability. We perform this analysis, which is fully described at the mathematical level in the Supporting Information, using functional data analysis. This study can be considered two-dimensional because each element is a complete I – V curve instead of a single V set and V reset value. Consequently, by considering the variability generated all along the I – V curves, a holistic perspective is achieved, and a more exhaustive variability estimation can be performed.…”
Section: Introductionmentioning
confidence: 99%
“…In this manner, different curves with the same V set and V reset lead to a non-negligible variability. We perform this analysis, which is fully described at the mathematical level in the Supporting Information, using functional data analysis. This study can be considered two-dimensional because each element is a complete I – V curve instead of a single V set and V reset value. Consequently, by considering the variability generated all along the I – V curves, a holistic perspective is achieved, and a more exhaustive variability estimation can be performed.…”
Section: Introductionmentioning
confidence: 99%
“…The basic principle of ANOVA is to decompose the total variance into between-group variance and within-group variance, and then calculate the ratio of the two, known as the F-statistic [42]. A larger F-statistic indicates a greater proportion of between-group variance to the total variance, which means that the difference in means between each group is more significant.…”
Section: Anova Experimentsmentioning
confidence: 99%