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Images in (a) illustrate a normal sampling scenario, while images in (b) and (c) show how combined sampling is able to overcome bad (b) motion-based and (c) appearance-based measurements.
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However, the significant association observed in the joint dataset reduced significance of the results from the Spanish sample, therefore suggesting that the positive finding in the combined sample is mainly due to the SNP distribution in the Spanish sample.
The composition of the two sub-samples and the combined sample is given in Table 1.
In their paper, these authors provide evidence that the analysis of a combined sample is less prone to false positives than the separate analysis of replication samples.
The combined sample is then hybridized to the microarray and imaged, which results in the test and reference intensities for all the markers.
Contrary to the result of the GRR test in sample 1, which suggested a recessive effect of the ITGAV rs3738919-C allele, the result of the larger combined sample is more in favour of a dominant effect of this marker.
Yet the patterns of items for components were very similar across groups when the analysis of each group was limited to four components, so the combined sample is used to describe the components (Table 2).
Whilst the age-distribution is normal within each of the two otherwise identical studies, the age-distribution of the combined samples is not quite normal, as it shows two peaks.
Selected characteristics of subjects from NTDB, NVDRS, and the combined sample are shown in Table 2.
The gas bearing coal-sandstone combined samples were subjected to unloading tests, including unloading confining pressure (UCP) under constant axial tests and UCP-reloading axial stress (UCP-RAS) tests.
However, studies using multivariate analysis on combined samples are rare and further investigations using this approach are warranted [31].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com