To analyze correlates of the copeptin level on admission, the STATA validation bootstrapping program, SWBOOT, was used to perform 100 bootstrapped repeats of multi-variable stepwise linear regression on candidate correlates of copeptin levels.
After verification of the absence of the colinearity among the independent variables, stepwise linear regression model was applied to investigate the influential factors of the anatomical parameters of the isthmus.
After verification of the absence of the collinearity among the independent variables, stepwise linear regression model was applied to investigate the influential factors of the RFC and the banking angle.
The relevant sociodemographic variables (Table 1) were entered as input variables in stepwise linear and logistic regression models to predict IES scores, mental health, and vitality QOL scores and various psychological effects (e.g., whether one had trouble falling asleep) (Tables A2 and A3).
The independent predictors of these variables using stepwise linear regression showed that for each marker a measure of adiposity explained the largest amount of variance (17 28%) and that further metabolic syndrome components were additional independent predictors.
Therefore we subjected CAG-index, parental age of onset as well as paternal vs. maternal transmission as independent variables to a stepwise linear regression analysis with the Ne/ERN as dependent variable.
The possible risk factors and biochemical markers were entered as independent variables in a stepwise linear regression analysis.
We included these drugs as independent variables during the stepwise linear regression and found that they did not significantly affect our results.
We used age, education level, hypertension (n = 265), diabetes mellitus (n = 266), hyperlipidemia (n = 260), and obstructive sleep apnea (n = 228, represented by snoring) as independent variables in multiple stepwise linear regression analyses.
In order to exclude the possible confounding effect of vascular risk factors on the total WMH and MTA scores, we used hypertension, hyperlipidemia, diabetes mellitus [ 31], and obstructive sleep apnea [ 32] as independent variables in multiple stepwise linear regression analyses and found that in addition to old age, diabetes mellitus is the only risk factor that was related to total WMH scores.
Analyses for the continuous variables were conducted using stepwise linear regression in which the baseline value of each outcome variable was entered in Step 1.
