This paper reviews some of the statistical methods available for controlling for body size differences in the interpretation of developmental changes in exercise performance. For cross-sectional data analysis simple per body mass ratio scaling continues to be widely used, but is frequently ineffective as the computed ratio remains correlated with body mass. Linear regression techniques may distinguish group differences more appropriately but, as illustrated, only allometric (log-linear regression) scaling appropriately removes body size differences while accommodating the heteroscedasticity common in exercise performance data. The analysis and interpretation of longitudinal data within an allometric framework is complex. More established methods such as ontogenetic allometry allow insights into individual size-function relationships but are unable to describe adequately population effects or changes in the magnitude of the response. The recently developed multilevel regression modeling technique represents a flexible and sensitive solution to such problems allowing both individual and group responses to be modeled concurrently.
The authors are with the Children’s Health and Exercise Research Centre at the University of Exeter, Exeter, EX1 2LU, UK.