We also tested the difference between the regression parameter estimates of amygdala volume with the behavioral variables and hippocampal volume with the behavioral variables, respectively.
The objective of the current paper was to examine the relationship between the c-statistic and the regression parameters and the variance of the explanatory variable in the case of a univariate logistic regression model.
In regression model 2, inclusion of LPL did not substantially change the regression parameters; however, the association between TG and 25(OH D was weakened when LPL was included in model 2. Table 4 presents association parameters (OR and 95% CI) of serum 25(OH D and LPL with IR and T2D from logistic regression models.
Moreover, the original parameter values were estimated on larger data sets of a more heterogeneous nature than the clinical trial data investigated in this study and thus we did not find it appropriate to change the regression parameters for the link between FPG/MPG and HbA1c reported in the original papers.
However, selection bias may also contribute to the increase in the absolute value of the regression parameter quantifying the association between exposure and birth weight when smaller buffers are considered.
We can compute the total indirect effect through the difference between these two regression parameters (C-C').
The Aikake Information Criterion AICC) and a modified likelihood ratio test [ 23] were used to test the significance of the between-subject variability in regression parameters.
For this purpose, we constructed a model to estimate Pagel's λin the response trait Y [ 37, 58] simultaneously with the estimation of linear regression parameters for the relation between X and Y.
In addition, we took advantage of the fact that, when the logistic regression parameter between a target phosphoprotein and one of its parents is set to zero by the Lasso logistic regression, we can effectively delete the edge between these two proteins--searching for network model through parameterization.
The nonlinear function is approximated in terms of the piecewise linear interpolation model with the look-up table parameters, which can be rewritten as a dot product between the regression vector and unknown parameter vector using membership function.
