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The comparability of results across the platforms was also examined using a rank correlation metric.
Additionally, we proved that the assumptions for using a rank correlation test are not met.
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Publication bias was assessed using a ranked correlation test [ 33], and by employing a weighted regression test [ 34]; however, given that the prevalence estimates are unlikely to be affected by publication bias [ 35], if present, publication bias would not be adjusted for.
Begg and Mazumdar [ 6] use a rank correlation test based on Kendall's tau, defined as The test involves evaluating C, the number of pairs of studies that are ranked in the same order with respect to the two factors t ∗ and v, and D, the number of pairs of studies that are ranked in the reverse order.
This weak effect is not detected when using
We also measured the correlation in selection frequencies using a spearman rank correlation.
Using a Spearman rank correlation coefficient, we found a significant correlation between all biomarkers (sFlt-1, PAI-1, sE-selectin, sICAM-1, and sVCAM-1).
Correlation between potential herd-level risk factors was assessed using a Spearman rank correlation matrix.
The numeric correlation between all candidate variables selected for a model was assessed using a Spearman rank correlation matrix.
Correlation between SSR reference sequence repeat number and allelic richness was performed using a Spearman rank correlation.
The correlations between the different parameters in the calcium-phosphate metabolism and sKlotho levels were evaluated using a Spearman rank correlation test.
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