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Adding variables in multivariate analysis made this effect disappear.
A multivariate analysis made in 709 patients by Deshpande et al. found low rate of total or partial flap necrosis (less than 1%) [ 4].
Multivariate analysis made it possible to see its association with better prognosis despite the NIHSS variable acting as a confounding factor.
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Splitting the spectral variation into successive, principal components, using multivariate analysis, makes the data more accessible: highlighting areas of the spectra that correlate with variances in quantitative measurements.
Multivariate genetic analysis makes it possible to ask questions about the genetic and environmental links between and within learning abilities and disabilities.
First, a multivariate analysis was made to examine the diversity of Tessekre's population.
This multivariate analysis was made on a restricted sample of 508 settlements with complete and consistent dataa (i.e. 86% of the total population).
To analyze factors associated with misdiagnosis a multivariate analysis was made using a multiple linear regression with diagnostic category as the dependent variable.
Multivariate analysis was made using Cox-hazard model analysis.
A univariate, but no multivariate, analysis was made for several factors (Grade 3).
To study the independent significance of MetS and DM for clinical outcome, multivariate analysis was made using an optimizing stepwise procedure based on the Bayesian approach.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com