The order order transition (OOT), the lattice disordering transition (LDT), and the order disorder transition (ODT) of SEBS were explored with a linear temperature increment ranging from 100 to 220 °C.
Fig. 8 Random sampling with 10%% of 337 permutations being explored with the linear and the bagging tree regression methods and the aggregate regressor.
Factors affecting utility difference were explored with multiple linear regression analysis.
Possible associations between infant blood lead and the independent variables were separately explored with bivariate linear regression models.
The correlation was further explored with a multiple linear regression analysis, and the covariance of the model R and the standardized correlation coefficient are presented.
The relation between IVF outcomes and quartiles of HCB, p, p´-DDE, and total DDT was explored with multivariable generalized linear regression models, with data structured to accommodate joint models for multiple outcomes and multiple cycles contributed per woman.
Following significant standard regression models at α = 0.01, the relationships for the 6 sub-groups of patients for explanation by 5 measures of biochemical ratios were explored with backward, step-wise, linear regression models.
Significant univariate correlations were explored with follow-up stepwise multiple linear regression models to determine if potential covariates (i.e., age, sex, body mass index, intervention group) influenced the associations.
In addition, it is shown that the specific characteristics of emotion episodes can be profitably explored with the help of non-linear dynamic systems theory.
The relationship between the various factors (age, gender, highest educational level achieved, group [SCD vs. AA], employment status) and depression was explored with a series of logistic regression models, and their relationship with loneliness was explored with multivariate linear regression.
