The abovementioned studies mainly investigated bivariate relationships between demographics, physiological variables, symptoms, physical function, and subjective health status, but lack a multivariate perspective on subjective health status in COPD.
It seeks to identify factors influencing this attitudes, using a multivariate perspective.
Given the complexity of the beef market in Argentina, it is interesting to analyze it from a multivariate perspective.
The association of these variables with distress scores from a multivariate perspective was also explored using multiple linear regression analyses.
In the multivariate perspective, [ 2] propose Global Test, modelling differential gene expression by means of random-effects logistic regression models, while [ 7] propose ANCOVA Global Test, which is similar to Global Test but with phenotype and genes exchanged in regression models.
Therefore, it is important to develop a method to simultaneously demonstrate the interactions of different molecules, so as to decipher the tumor biological behaviors from a multivariate perspective instead of a univariate perspective.
The risk factors have been extensively investigated [ 5- 7]; however, only a handful of studies have focused on the statistical associations between biochemical and clinical variables from a multivariate perspective [ 8- 10].
This is the first study to explore a multivariate perspective on subjective health status in COPD patients based on Wilson and Cleary's [ 4] conceptual model of biopsychosocial relationships to subjective health status.
Two multivariate methods, RF and PLS-DA, were shown to be useful to select the most informative items from a large set of testing instruments with high sensitivity and specificity, while allowing to characterize a set of 63 patients from a multivariate perspective.
Indeed, intraspecific and interspecific body size frequency distributions have played important roles in the development of these fields, and particularly of macroecology, which regularly adopts univariate (i.e. frequency distribution-based), bivariate and then multivariate perspectives to understanding large-scale spatial and temporal variation in body size, range size and abundance [8].
