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To investigate the relationship between disease status and cytokine levels, we performed a linear multivariate correlation study of natural log transformed cytokine levels and disease, after correcting for age and contact lens use, as covariates.
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A noticeable difference with other multivariate aggressiveness correlation studies is that this study attains the correlation in a setting with radiologist-indicated regions instead of pathology pre-defined regions of interest, which is more similar to regular clinical practice.
The present study has established several optics-based parameters to be used in a multivariate correlation with breast cancer patient outcome.
It is evident that this problem can not be solved by simple linear multivariate correlation.
Benefits and issues of multivariate correlation based calibration are evaluated during one year long measurement campaign.
Prospective cohort correlation study.
Design: Quantitative correlation study.
§ Pearsons correlation used for univariate correlation estimations and §§ partial rho correlations used for multivariate correlation estimations.
PCA can be viewed as a multivariate correlation analysis.
We used Pearson's linear correlation with CI 95% and a multivariate correlation.
The dominant methodologies can be segregated into region of interest-based or seed-based correlation studies and data-driven multivariate analysis techniques, such as independent component analysis (ICA), and are described in detail here.
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