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We used a multivariate analysis to identify factors independently affecting physician awareness of how best to manage ARGN infections.
We used a multivariate analysis for validation of the forest classification, i.e. Polythetic Agglomerative Hierarchical Clustering (PAHC) [34] with the software PRIMER v.5.
Instead of analysing each behavioural variable independently, we used a multivariate analysis of variance with repeated measures (MANOVAR, [28] [29]) to test for behavioural changes between the second and the third step of the experiment.
For this purpose, we used a multivariate analysis taking into account only variables observed at admission.
We used a multivariate analysis of variance (MANOVA) to examine behavioural performance in newborn offspring from the two treatments.
To develop predictive models, we used a multivariate analysis based on multiple linear regression as contained in the program AMOS version 5 (Small Waters Corp).
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The objective of the current research is to establish a predictive model of DLC properties using a multivariate analysis method.
The influence of the principal risk factors on prognosis were studied and their effect adjusted using a multivariate analysis based on the Cox proportional hazards model.
In this study the selection of in vivo predictive in vitro dissolution experimental set-ups using a multivariate analysis approach, in line with the Quality by Design (QbD) principles, is explored.
Data were classified according to the metabolic profile using a multivariate analysis in principal component analysis.
Possible associations between SUVmax values of vertebrae, pedicles, and facet joints were tested using a multivariate analysis of variance (ANOVA).
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