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Logistic regression is the most common statistical model for processing multivariate data in the medical literature.
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We found that this plot was capable of processing multivariate data to distinguish specific markers of the quality of machined surfaces, which are produced in ball end milling.
Robust dimensionality reduction is an important issue in processing multivariate data.
Logistic regression is mostly used in these studies in processing multivariate data.
A new method of processing multivariate response data to extract chemical information has been developed.
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Both in univariate and multivariate analyses COX-2 expression was significantly correlated with a worse survival independently of the algorithm used for processing the raw immunohistochemical data (Table 4, Figure 3).
Ligges, U. & Mächler, M. Scatterplot3d – an R package for visualizing multivariate data.
EMT: Exact Multinomial Test: Goodness-of-Fit Test for Discrete Multivariate data.
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