As there are 5912 observations spread over a 13 year age-range, there is sufficient data to provide estimates of the means of the variables at one-tenth year intervals and to provide estimates of the mean rates of change of the variables as well. Since 90% of the successive observations of individuals have an interval of greater than 1.75 years, no longitudinal modeling at the shorter time scale (6 months) at which significant changes in the measured variables can occur is possible. (The estimate for the time scale is derived from Sullivan et al. (2011)). Results are not independent between models for different ages since the data in each of the 131 regression models has considerable overlap with the data used in the models for nearby ages. Significance levels and effect sizes were obtained from the regression calculations and corroborated using a non-parametric bootstrap method with 1000 resamplings. The bootstrapping process is described in Chorlian et al. (2017, p. 28). The regression method used in the calculation of the genotypic effect on the trajectories has the power to reliably detect effect
