However, quality of life score was significantly improved in former group after adjustment for confounders using the multivariate linear regression modeling (Table 5).
Using the multivariate linear regression model, assessing the relation between the xenohormone transactivities and the POPs the impact of the lifestyle characteristics were evaluated by entering variables together with the POPs.
Therefore, the variables that are used for the multivariate linear regression analysis are: land area, coastline, total number of SSS ports (SSS ports), number of small SSS ports (sSSS ports), number of large SSS ports (lSSS ports), number of inhabitants, GDP, GDP per head, road length and rail length.
Tumour size was transformed using natural logarithm to obtain a better distribution for use in the multivariate linear regression models.
A total of 53 features (7 first-order descriptors, 24 Haralick features, 20 Galloway features and 2 local binary pattern features) were extracted from each muscle region of interest (ROI) and were used to perform the multivariate linear regression analysis (MANOVA).
Using the methodology of Cavrini and associates and Sitoh and colleagues [ 18, 19], an ordinal variable for the EQ-5D index was created by categorizing the continuous variable into 4 levels, and an ordered logit regression model was used to confirm the multivariate linear regression.
To analyze growth, repeated measurement analysis was applied using the multivariate general linear model (GLM) [ 15].
All dependent variables were used as approximately continuous parameters in the multivariate linear regression models.
In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox.
We used a multivariate linear regressor for the FTP (for patients with time till next relapse < 500).
