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.
A careful analysis of this approach is presented, also including the situation where the model contains a linear parametric trend, which requires specific treatments.
Suppose, for example, that it is suspected that the outcome of interest, say wages, and the imputed proficiency values are statistically associated in non-linear ways, and so the secondary analyst's model contains non-linear transformation of the outcome variable or one or more of the independent variables; however, the latent regression does not include such terms.
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.
The model contains an additive, linear submodel for sources, and multiplicative exponential terms for the attenuation and transport variables that act directly on the source terms.
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.
