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Exact(5)
However, these models were not significantly better than the models without interaction terms.
Since, for each pair of loci, the two-factor analyses implicated additive models as the most parsimonious and to keep the number of parameters as small as possible we only fit three-factor additive models without interaction (ADD1, ADD2, ADD3, ADD12, ADD13, ADD23, and ADD123).
Therefore, we use the parsimonious models without interaction term.
Among the 65536 models without interaction, 36 had a ΔAIC < 4.
The interaction between chlorpyrifos and imidacloprid was not significant at the 5% level for any of the analyses, and therefore we report results of fitting the models without interaction.
Similar(55)
Since all the other interactions were not significant, and the conclusions for all the other variables did not change when including or excluding interactions, only the more parsimonious models without interactions are reported in the paper.
An initial support to this application came from the results above showing incorporating cooperative interactions were more predictive than simple models without interactions (Table 1).
The estimates were derived from models without interactions.
Models without interactions might conceal gender differences in the effects of individual predictors of transition to DP.
Thus, we also compared the average heart rate values throughout the entire exposure time periods (Wald tests in mixed models) without interactions terms for time.
Although Table 3 showed that inclusion of the interaction term (G×E) explained the largest proportion of variability in models 6 and 8, this did not produce a large increase in the prediction ability of these two models over that of the models without interactions (models 1, 2, and 4).
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