Note: "Ref" indicates the reference category for the discrete variable in the multivariate regression models.
The PCA technique was employed in order to omit the correlation between the independent variables in the multivariate regression.
In the multivariate regression analyses, backward elimination approach was used to determine independent risk factors for HRQoL including self-reported general health.
We found that the transverse dimension had a significant influence in treatment duration and number of appointments in the multivariate regression models.
The many other covariates BMI, physical activity behaviour, resilience, personality traits, educational level, and migration background proved statistically insignificant in the multivariate regression analysis of the present study.
The effects of this are visible in the multivariate regression models with an increasing negative impact of summer temperatures on yields.
By invoking the variable selection procedure embedded in the multivariate regression analysis, the significance of variables to the responses was assessed.
Figure 2B shows the relative importance of each factor in the multivariate regression model for protein expression levels.
Significant variables from the univariate analysis were included in the multivariate regression analysis to determine whether facility characteristics were associated with survival for all gynecologic malignancies.
SVA allows more accurate FDR estimates to be obtained by including potentially hidden (i.e unknown) in addition to known confounding factors in the multivariate regression [31], [32].
Log values were used in the multivariate regression analysis.
