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Descriptive statistics and the multivariate analysis have been used to explore underlying structures of the data collected.
Two types of data analysis approaches, univariate analysis and multivariate analysis, have been widely used in metabolomics projects, including most of the CF related studies referenced in this paper.
The results of the multivariate analysis have two main implications.
Recent studies using multivariate analysis have reported conflicting results, however.
For these reasons, several strategies for estimating RRs in multivariate analysis have been proposed [ 7, 14- 16].
Other recent studies which did not use Freesurfer as input for multivariate analysis have also found results in line with ours.
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Multivariate analysis has failed to identify a significant effect of CVC removal on the prognosis for patients with candidaemia.
Spatial and multivariate analysis has been undertaken to highlight differences in characteristics of public school districts with and without wind turbines.
The condition and physicochemical properties of materials gained through NIR and multivariate analysis has been widely researched in agriculture, the textile industry, as well as in cultural heritage for historic silk and cellulosic materials [34 39].
Multivariate analysis has already been successfully used to assess the stress and welfare of fish but has never been employed solely for the monitoring of physiological parameters (Adams et al. 2007; Di Marco et al. 2008; North et al. 2006; Turnbull et al. 2005).
In multivariate analysis, having male-female sex (compared with male-male sex) was associated (p<0.05) with increased risk of not having repeat confirmatory testing.
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