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- Title
Peak-Power Estimation Equations in 12- to 16-Year-Old Children: Comparing Linear with Allometric Models.
- Authors
Duncan, Michael J.; Hankey, Joanne; Nevill, Alan M.
- Abstract
This study examined the efficacy of peak-power estimation equations in children using force platform data and determined whether allometric modeling offers a sounder alternative to estimating peak power in pediatric samples. Ninety one boys and girls aged 12-16 years performed 3 countermovement jumps (CMJ) on a force platform. Estimated peak power (PPest) was determined using the Harman et al., Sayers SJ, Sayers CMJ, and Canavan and Vescovi equations. All 4 equations were associated with actual peak power (r = 0.893-0.909. all p < .01). There were significant differences between PPest, using the Harman et al., Sayers SJ, and Sayers CMJ equations (p < .05) and actual peak power (PPactual). ANCOVA also indicated sex and age effect for PPactual(p < .01). Following a random two-thirds to one-third split of participants, an additive linear model (p = .0001) predicted PPactual (adjusted R2 = .866) from body mass and CMJ height in the two-thirds split (n = 60). An allometric model using CMJ height, body mass, and age was then developed with this sample, which predicted 88.8% of the variance in PPactual (p < .0001, adjusted R2 = .888) The regression equations were cross-validated using the one-third split sample (n = 31), evidencing a significant positive relationship (r = .910, p = .001) and no significant difference (p = .151) between PPactual and PPest, using this equation. The allometric and linear models determined from this study provide accurate models to estimate peak power in children.
- Subjects
ALLOMETRY; ANALYSIS of covariance; COMPARATIVE studies; STATISTICAL correlation; EXERCISE tests; MATHEMATICS; PROBABILITY theory; REGRESSION analysis; STATISTICAL sampling; T-test (Statistics); STATISTICAL power analysis; MULTIPLE regression analysis; EFFECT sizes (Statistics); BODY movement; RESEARCH methodology evaluation; DATA analysis software
- Publication
Pediatric Exercise Science, 2013, Vol 25, Issue 3, p385
- ISSN
0899-8493
- Publication type
Article
- DOI
10.1123/pes.25.3.385