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The experimental data were discussed and used to analyze the factors' main effect, interaction and optimization of the process.
Table 5 shows the hierarchical regression results of the main effect, interaction effect and control effect.
In this section, six different kinds of plots will be presented (i.e., Pareto plot, main effect, interaction between variables, response surface, contour and observed vs. predicted plots).
Three-dimensional response plot shown in Fig. 2a describes the behavior of cellulase production, main effect, interaction effect, and squared effect (nonlinear) of MgSO4 and pH at different concentrations.
The factors affecting the removal of phenol by adsorption onto R. stricta activated carbon were evaluated using factorial plots including main effect, interaction effect, the Pareto chart and normal probability plots.
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All main effects and trait × main effect interactions were included.
A three-factor, three-level Box-Behnken design was used to optimize and evaluate the main effects, interaction effects, and quadratic effects.
The polynomial equations comprise the coefficients for intercept, first-order main effects, interaction terms, and higher order effects.
One approach to overcoming this weakness is to use methods in the first stage that will identify variants with main effects, interaction effects, and both main and interaction effects.
Besides the four main effects, interaction effects were modeled for Series × Electrode Type, Series × NoP, Electrode Type × NoP, and Series × Electrode Type × NoP.
The results of the separate stratified analyses were successively assessed with Poisson additive models (Wood, 2006), including main effects, interaction terms, and non-linear temporal trends simultaneously.
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