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In recent years, a number of studies have demonstrated the possibility to discriminate retrieval of conceptual categories in functional MRI data, using multivariate analysis methods [25] [28].
The purpose of writing this software was to help users in the analysis of microarray data using multivariate analysis methods.
Systematic studies of the metabolic state of biological systems using multivariate analysis methods are referred to as metabolomics.
Using multivariate analysis methods we examined the short-time evolution of neural representations of indirect objects retrieved during reward-learning about direct objects.
This could be achieved by utilising multiple relevant IHC biomarkers combined with using multivariate analysis methods to facilitate reliable stratification and exploit the broad dynamic range of IHC data.
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With this number of analytes, the information would be useful for both regulatory actions as well as for source identification using multivariate analysis or other "fingerprinting" methods.
Using cluster membership as an independent variable, we compared study strategies, self-study hours, exhaustion from study, ECs and GPAs using multivariate analysis of covariance (MANCOVA) method.
Here, we describe a method using multivariate analysis.
We then searched for possible confounding variables using multivariate analysis and a forward stepwise method; variables were entered into the equation if the significance of the association on univariate analysis, P, was <0.1.
Data were compared by using multivariate analysis of variance and Scheffé's method.
Furthermore, three related methods are used: multivariate analysis (using the statistical package SPSS), the principal components analysis1, factor and cluster analysis, in order to investigate the possible groups resulting, regarding the types of transport and also time groups.
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CEO of Professional Science Editing for Scientists @ prosciediting.com