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Data were analyzed with a polynomial mixed model containing linear, quadratic, and 2-factor interactions for Ile, Leu, Met, and Thr, and cow and residual as random factors.
The experiments were randomly performed for each factor on three levels using a Box Behnken design, which provided enough information to calculate the regression model containing linear, interactions, and curved factor effects.
The experiments were performed in a random order on three levels for each factor using a face-centered cube central composite response surface design (Table 2) that provides enough information for calculation of the regression model containing linear, interactions, and curved factor effects.
Multiple linear regression model containing linear terms for all six predictor variables (table rows) and adjusting for age (odor naming and odor interpretation) and gender (odor naming), significances (Bonferroni p≤0.025) in boldface.
We compared the BMI-mortality curves derived using the MFP method with the continuous BMI model containing linear and quadratic BMI terms and the categorical model based on WHO BMI classifications.
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This model contains linear terms of the variables of interest and possibly also cross-product terms to describe interaction effects.
Therefore, a linear mixed model containing both linear and second order time components as fixed effects (growth model) as well as random effects for intercepts and slopes for time was estimated first.
For the proposed system, we construct a novel actuator fault model containing both linear and nonlinear terms which is more general than the conventional actuator fault models.
For nonlinear model containing a linear substructure, two Rao-Blackwellized particle filtering algorithms have been presented in [131] to yield efficient execution and high accuracy, respectively.
A regression model containing three linear (β1, β2, β3), three quadratic (β11, β22, β33), three interaction (β12, β23, β13), and intercept β0 terms is used.
The initial gloss of mixtures containing UA, CR inorg), ZnO, AlSt, and linseed oil can be described by a reduced model containing the linear mixture (p < 0.0001), the interaction between UA and CR inorg) ('A B', p = 0.0492), and the interaction between UA and ZnO ('A C', p = 0.0014), illustrated in Fig. 2.
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