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Interactions between two factors have significant effects on several of the measured responses.
λ Interactions between two factors.
Interactions between two factors could appear as an antagonistic effect (negative coefficient) or a synergistic effect (positive coefficient).
We also performed homogeneity test and logistic regression analysis to estimate and compare the risks between the strata and interactions between two factors, respectively.
Statistical significance for interactions between two factors was tested using the likelihood ratio test comparing a model with the cross-product term to one without.
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In this work, we illustrate the issues encountered in constructing kernels for investigating interactions between two factor-sets, and propose a simple yet intuitive solution to construct the G×E kernel that retains the ease-of-interpretation of classic regression.
Current approaches for examining effect profiles in Multi-G-Multi-E analyses are either underpowered due to large degrees of freedom, ill-suited for detecting G×E interactions due to imprecise modeling of the G and E effects, or lack of capacity for modeling interactions between two factor-sets (e.g., existing methods focus primarily on a single E factor).
The design of experiments were performed using four factor-three-level central composite design coupled with response surface methodology to evaluate the interaction between two factors in order to determine the optimum process conditions.
Test adopts fuzzy orthogonal method to analyze the main effects and the interaction between two factors, taking tensile strength, diameter variety rate and pH value of indicator as evaluation index.
Evan Braden Montgomery draws on different strands of realist theory to develop a novel framework that explains why leading states have accommodated some rising regional powers but opposed others.Montgomery examines the interaction between two factors: the type of local order that a leading state prefers and the type of local power shift that appears to be taking place.
From the equation, interaction between two factors was also found.
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