The serial data from two siblings, aged 6.6 and 7.5 years of age at the initiation of the study, measured each evening for total standing height during 365 days, are analysed by two methods to investigate the nature of the underlying growth pattern. The saltation and stasis model, designed to identify the presence of statistically significant pulses in sequential data, is compared for goodness-of-fit to first to sixth degree polynomial functions, used to investigate the presence of a slowly varying smooth continuous function in the data, and high order polynomials of the same degree of flexibility as the individual's saltation and stasis results. The saltation and stasis model is found to better-fit the experimental data than the slowly varying smooth continuous functions (p < 0.01 to 0.001). The timing characteristics of the saltation and stasis patterns are investigated and the temporal patterns are suggestive of a non-random, aperiodical deterministic system.
Algorithms Analysis of Variance