In these panel-data models it is postulated that the Gini coefficient, as a dependent variable, is a function of a set of independent variables: economic losses, GDP, proportion of people aged 65 and over, proportion of nonwhite population, political dominance of the U.S. Senate, time trend, and cross-sectional dummies.
Each HRQoL subscale was used as a dependent variable as a function of time and covariates: age, gender, number of comorbidities, average length of stay and re-hospitalization in 30 days.
An equation of each dependent variable as a function of cooking variables (independent variables) was obtained by multiple non-linear regression using the least square method by MATLAB software for developing of empirical models.
In the present study, the validation of the mediation model implies that the effects of training type (categorical independent variable, MCT = 1, PRT = 2) on post-training changes in each executive function variable (dependent variable), is "explained" by post-training changes in physical fitness (mediator).
We modelled the probability of position change (%, dependent variable) as a function of seven explanatory variables (fixed effects) accounting for the number of variables (10 12) and for differences in amount of IVE between explanatory variables (Table 4).
(4) Minimize w, b, ξ, ξ * 1 2 w 2 + C ∑ i = 1 n (ξ i + ξ i * ) Subject to: (5) y i - w, x i - b ≤ ε + ξ i w, x i + b - y i ≤ ε + ξ i * ε, ξ i, ξ i * ≥ 0 If the space of the original data doesn't have a linear relationship with the dependent variable, the function f is reformulated from the primal model to the dual model Expression 6).
This allows for expressing a subset of the quantities, defined as the dependent variables, as a function of the remaining, free variables.
The design conditions are obtained by means of a parameter-dependent Lyapunov function and extra variables for the filter design, expressed as bilinear matrix inequalities.
The presence of an error-correction term among a number of co-integrated variables shows that changes in the dependent variable is a function of both the level of disequilibrium in the co-integration relationship (represented by the ECM) and the changes in other explanatory variables.
State and control variables are certainly nonnegative time-dependent functions.
In the multiple linear regression, taking the global QoL as the dependent variable, family function (beta = 0.139) and to be spouse (beta = -0.461) remained in the equation.
