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We then introduce the characteristic length to scale the eigencompliances and compliance matrices to compare translational compliances with rotational ones.
Finally, we constructed matrices to compare how support differed by relationship type (i.e. partner vs. family).
The salient patterns and themes were further explored using matrices to compare findings across subgroups and to eventually guide the outline of the manuscript.
Finally, data were extracted into summary matrices to compare internal and external contextual factors influencing PRC decision-making across the five cases [ 33].
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We then developed our matrix to compare these individual metrics, and using this matrix, we compared different subjects to one another.
For a particular classifier, various standard performance metrics can be summarized based on the confusion matrix to compare model prediction performance.
We used the well-known BLOSUM62 substitution matrix to compare amino acid residues of "ancestral" sequences.
In addition, analyses based on the three-codon positions in matR were also conducted on 174-taxon matR matrix to compare variation and phylogenetic signal.
For example, [ 1] used a singular value analysis (SVA) of the sensitivity matrix (there called "weight matrix") to compare measurement setups which differed either in the optode spacing or the measurement type (reflectance vs. transmittance setup).
The primary analysis utilized logistic regression with generalized estimating equations with an exchangeable correlation matrix to compare the presence of detectable HIV-1 RNA in vaginal secretions across the three visits, using the pre-infection visit as the baseline.
Dynamic binding capacity assays were accomplished to characterize this matrix and to compare with commercial resins.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com