Sentence examples for multifactor analysis this from inspiring English sources

Both CT and PET responses were individually significantly associated with survival duration; but in the multifactor analysis, this included the known prognostic factors of CT response, performance status, weight loss, and stage; only the PET response was significantly associated with the duration of survival (p < 0.0001) [ 12].

The multifactor analysis of this study identified age, liver and cardiac involvement as independent prognostic risk factors.

In this paper, we separately address the advantages and disadvantages of multifactor analysis and discriminant analysis and propose Multifactor Discriminant Analysis (MDA) by synthesizing both methods.

"Judicial attempts to fashion a civil definition of 'minister' through a bright-line test or multifactor analysis risk disadvantaging those religious groups whose beliefs, practices and membership are outside of the 'mainstream' or unpalatable to some".

This seems to be because Multifactor Discriminant Analysis offers the combined virtues of both multifactor analysis methods and discriminant analysis methods.

Multifactor Discriminant Analysis can be thought of as an extension of LDA to multiple factor frameworks providing both multifactor analysis and discriminant analysis.

Moreover, Multifactor Discriminant Analysis (MDA), like MPCA, uses multifactor analysis and calculates subject parameters that represent the characteristics of subjects and are invariant to other changes, such as viewpoints or lighting conditions.

Section 3 first addresses the advantages and disadvantages of multifactor analysis and discriminant analysis individually, and then Section 4 proposes MDA with the combined virtues of both methods.

MDA can be thought of as an extension of LDA to multiple factor frameworks providing both multifactor analysis and discriminant analysis.

Statistical design of experimental methodology based on Taguchi orthogonal design has been used to study and optimize various parameters using multifactor analysis of variance (ANOVA).

It deals with the factorial experiments that are carried out within blocks, an analog of the multifactor analysis of variance (ANOVA), and classifies repeated measures designs by the number of between-subject and within-subject factors.