For the majority of children, the frequency of hyperactive symptoms decreased or remained low from 2 to 7 years. However, 7 children in 100 were classified as having high initial levels of hyperactive symptoms that persisted over time. Several prenatal and early postnatal risk factors identified these children, although additional variables will need to be identified to accurately predict high and persistent hyperactivity. Findings suggest that preventive interventions could target high-risk families during pregnancy and early childhood.

In the literature on tests of normality, much concern has been expressed over the problems associated with residual‐based procedures. Indeed, the specialized tables of critical points which are needed to perform the tests have been derived for the location‐scale model; hence, reliance on available significance points in the context of regression models may cause size distortions. We propose a general solution to the problem of controlling the size of normality tests for the disturbances of standard linear regressions, which is based on using the technique of Monte Carlo tests. We study procedures based on 11 well‐known test statistics: the Kolmogorov–Smirnov, Anderson–Darling, Cramér–von Mises, Shapiro–Wilk, Jarque–Bera and D’Agostino criteria. Evidence from a simulation study is reported showing that the usual critical values lead to severe size problems (over‐rejections or under‐rejections). In contrast, we show that Monte Carlo tests achieve perfect size control for any design matrix and have good power.

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