Linear multivariate regression analysis displayed that MAGE and average diurnal cortisol fall were uniquely associated with some cognitive parameters, such as AVLT trial, FAS, and TMT (P < 0.05). Conclusion-Glucose fluctuation was strongly associated with cognitive impairment in elderly type 2 diabetes...
What is multivariate analysis of variance (MANOVA)? When is it used? Give an example. How does linear regression differ from analysis of variance? Is logistic regression sensitive to outliers? If not, why not? If so, how? x 420 610 625 500 400 450 550 650 480 565 ...
The linear mixed models were performed with the lme4 R package (v 1.1-31). The multivariate SPLS models were performed with the caret R package (v 6.0-92). P values were corrected for multiple testing by the Benjamin–Hochberg false discovery rate (q value). Features with q < 0.1 ...
Therefore, like Mackenbach and colleagues (Mackenbach et al., 2017), we estimate multivariate linear regression models with the Rate Ratio of educational inequality as the dependent variable, inequalities in political participation as the primary independent variable, and a series of potentially ...
Multivariate fMRI analysis of postextinction pattern reactivation The multivoxel patterns evoked by the first five US omissions at CS+ and CS− offset in the vmPFC region of interest (ROI; Harvard-Oxford Atlas, Harvard Center for Morphometric Analysis, thresholded at 50% tissue probability) were ...
The study was performed using a combination of open-source softwares for genomic and multivariate statistical analysis, all cited within the Methods section. In-house scripts used to analyse data are available on Figshare at 10.6084/m9.figshare.24975591. ...
We utilized partial least squares regression analysis (PLSR) as the appropriate multivariate technique to analyze numerous potential explanatory variables for species with a limited number of individuals. PLSR identifies components that are linear combinations of many correlated predictors and can maximize th...
First, data were screened for multivariate outliers by means of Mahalanobis distances. Two participants from the parent condition were subsequently excluded, resulting in n = 65 tutees in the parent condition and n = 64 in the volunteer condition. Second, descriptive analyses and group comparisons ...
For both linear SVM and logistic regression, each of the parameters of the models provides a measure of the degree by which each feature skews the likelihood that a test sample should be classified with a given label or not. Hence, the risk class prediction is the result of the weighted ...
(nonlinear Causal Relationship Estimation by Artificial Neural Network) method55,56. The nCREANN is a multivariate approach that utilizes artificial neural network (ANN) to estimate effective connectivity among multiple regions. The nCREANN is based on a nonlinear Multivariate Autoregressive (MVAR) model...