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Spearman's correlation and multiple regression analyses were used to evaluate bivariate and multivariate relationships, respectively.
Spearman's correlation and multiple regression analyses were used to evaluate bivariate and multivariate relationships, respectively, and χ was used to evaluate nonparametric variables.
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Linear regressions, with skewed variables were ln transformed, and logistic regressions were used to test for multivariate relationships with continuous and dichotomous variables, respectively.
Bivariate and multivariate relationships between risk factors and incident depression (GMS AGECAT) were studied.
Multivariate relationships were evaluated using a general estimating equation model.
The input-output relationship being modelled is univariate which is quite simple, unlike complex multivariate relationships.
VEC models are widely used to estimate short-and long-run multivariate relationships.
Canonical correspondence analysis (CCA) was used to determine multivariate relationships between DGGE banding profiles and environmental factors.
These strong relationships remained in multivariate relationships (Table 4).
First, we used principal component analysis to characterize multivariate relationships between C, O, N and S content, DNA GC content, protein length, and the proportions of hydrophobic, polar, positive, negative and aromatic residues, respectively, in the entire dataset.
The plot depicts multivariate relationships among the European mink sampled.
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