A fairly high variance was found in the number of children in a household.
In MnB, the majority of variance was found to be between subjects (94%), while in MnP and MnU the majority of variance was found to be within subjects (79% and 99%, respectively), even when controlling for timing of sample.
Subject variance was found to dominate the metabolomics data although the variations in subject age and BMI were very small.
At below-barrier energies, the mass variance was found to increase with decrease in energy for both nuclei.
If heterogeneity of variance was found, the variance function (varIdent) was used to model heteroscedasticity to avoid transformations.
The largest variance was found in costs assigned to an ADE (ADE range, adjusted to 2014: €10799 (Rottenkolber [25])–€7177 (Bates [25]).
A positive correlation between Attachment Disorder symptoms and other mental health problems (as rated by carer-report Strengths and Difficulties Questionnaire Total Difficulties Score), accounting for 36% of the variance was found, with a large effect size (rs = 0.60).
Although the basic tendency was the same, i.e., a small coefficient variance was found by using feature regions with weight coefficient (g_j), the SIFT feature showed better performance compared with the proposed method.
In the analysis of the final model of the stepwise multiple linear regression containing 6 independent variables, household income which explained 72% of the variance was found to be the most influential variable followed by respondents' age and gender, access to information on organic vegetables, household member with health problems, and household location (Table 5).
In the analysis using the stepwise multiple linear regression final model with 5 independent variables, household income which explained 66% of the variance, was found to be the most influential variable followed by gender and age of respondents, access to information on organic agriculture, and presence of household member with a health problems (Table 3).
