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The SOM classified the reservoirs into six clusters, from least to most polluted, with differences in physicochemical and hydrogeomorphometry variables between clusters.
Bridge maps were generated to explore the relative agreement on rating variables between clusters and across provider and patient groups.
Two-sided t-tests (assuming equal variance) and chi-squared/Fisher's exact tests were used to test for statistical significant differences in phenotypic variables between clusters.
Comparing correlation coefficients of matching pairs of variables between clusters revealed differences predictive of life and death and disparate physiologic relationships depending on injury and resuscitation state.
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The gene content of each cluster is variable between clusters present at different chromosomal loci, but largely conserved among clusters located at the same chromosomal locus.
Each variable within the clustering solution was included in a subsequent multivariate analysis of variance (MANOVA) comparing the three clusters in order to determine the relative contribution of each variable between clusters [ 46].
The landform, altitude and grazing intensity were found to be the most important variables distinguishing between clusters.
However, although most of the variables had unequal variances between clusters, conducting non-parametric tests produced the same results and subsequently only the parametric results are reported.
The magnitude of the F values from the analysis of variance performed on each dimension is an important indication of how well the respective variable discriminates between clusters.
Stratification of this primary outcome variable reduces the between-cluster variability in the primary outcome.
There was no significant difference in age, gender, or other demographic variables between the two clusters (data not shown).
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