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Values on X associated with non-significant/significant effects, giving regions of non-significance and significance, is provided by the Johnson�CNeyman approach (Fig. 1). The Johnson�CNeyman technique is the strongest alternative to ANCOVA in experimental designs when the assumption of homogeneity of regression slopes has been violated (39). The basic difference between ANCOVA and the Johnson�CNeyman approach is that the effects are estimated at the grand covariate mean with ANCOVA, but with the Johnson�CNeyman technique the effects are estimated as a function of the covariate score. The Johnson�CNeyman technique was used to analyse the heterogeneous regression cases (40), and a ��Quick Johnson�CNeyman Procedure Calculator�� was used to calculate the regions of non-significance and significance for separate educational levels (http://www2.gsu.edu/~epstco/). AZD0530 solubility dmso GDC-0941 order The regions of significance may lie outside the range of the covariate scores included in the sample, resulting in no region of significance within the range of sample data (40). Fig. 1 The Johnson-Neyman technique. When heterogeneous regression slopes are present this implies that the magnitude of the intervention effect (Y) is not the same at different levels of X (covariate; the baseline intake in these analyses). The Johnson-Neyman ... The significance level was set at Pdiglyceride intervention and control groups. However, for the mothers and fathers there were significant differences with regards to the educational level (both mothers and fathers), intake of sugar-sweetened fruit drinks (mothers) and intake of soft drinks and vegetables (fathers) (Table 2). Table 1 Adolescent baseline characteristics (demographic and behaviour) for the control and the intervention group in the HEIA study Table 2 Parental baseline characteristics (demographic and behaviour) for the control and the intervention group in the HEIA study, female and male Significant differences were found for the adolescents at the post-intervention assessment between the intervention group and the control group in fruit consumption (P