The appropriateness of normalizing data, as one method to reduce the effects of a covariate on a dependent variable, should be evaluated. Using ratio, 0.67-nonlinear, and fitted normalizations, the aim of this study was to investigate the relationship between ground reaction force variables and body mass (BM). Ground reaction forces were recorded for 40 female subjects running at 3.7 +/- 0.18 m x s(-1) (mass = 58 +/- 6 kg). The explained variance for mass to forces (peak-impact-vertical = 70%; propulsive-vertical = 27%; braking = 40%) was reduced to <0.1% for mass to ratio normalized forces (i.e., forces/BM1) with statistically significantly different power exponents (p < 0.05). The smaller covariate effect of mass on loading rate variables of 2-16% was better removed through fitted normalization (e.g., vertical-instantaneous-loading rate/ BM(0.69+/-0.93); +/-95% CI) with nonlinear power exponents ranging from 0.51 to 1.13. Generally, these were similar to 0.67 as predicted through dimensionality theory, but, owing to the large confidence intervals, these power exponents were not statistically significantly different from absolute or ratio normalized data (p > 0.05). Further work is warranted to identify the appropriate method to normalize loading rates either to mass or to another covariate. Ratio normalization of forces to mass, as predicted through Newtonian mechanics, is recommended for comparing subjects of different masses.
[1]
K P George,et al.
Allometric scaling of left ventricular mass by body dimensions in males and females.
,
1997,
Medicine and science in sports and exercise.
[2]
T. Craven,et al.
Etiologic factors associated with anterior knee pain in distance runners.
,
2000,
Medicine and science in sports and exercise.
[3]
Hilary M. Clayton,et al.
Effects of Offset-Normalizing Techniques on Variability in Motion Analysis Data
,
2004
.
[4]
R. Bartlett,et al.
Research design and statistics in biomechanics and motor control
,
2001,
Journal of sports sciences.
[5]
B. Tabachnick,et al.
Using Multivariate Statistics
,
1983
.