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An intersection between the two regression lines was calculated.
There was a significant difference between the two regression coefficients (t = 7.58; p < 0.001).
However, β2 was not significant (P = 0.9174) between the two regression intercepts.
The difference between the two regression slopes indicated the relative influence of maternal or paternal effects.
The P value then represents the probability that the difference between the two regression estimates is purely due to chance.
For this test, the null hypothesis (H0) assumes that there is no significant difference between the two regression coefficients.
Similar(43)
The regression curves for total root length and RCD showed a separation between the two regressions but an unpaired, two tailed, t test of the slopes for the >2- and >5-mm root size classes showed no difference (P = 0.178) between the two size groupings, and this was also the case for root biomass (P = 0.741).
We then tested for differences in slope between the two regressions lines using a t-test.
The comparison between the two regressions was performed by means of a variation of the F-test, which is called the Chow test; it allows the verification of the equality between the rates of growth in the dependent variable [ 14].
The portion of the equation (3) C 1 = r Z ˜ e Z ˜ s is the correlation between the residuals of the two regression equations, e.g., 1 – p("at risk").
Although we observed no difference between the slopes of the two regression lines (0.97 ± 0.27 for group B vs. 0.86 ± 0.10 for group C), a shift between the intercepts of the two regression lines was evident.
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