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All the analyses included the expansion of data by sample weight, and correction of the variance by the sampling design used.
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The fall in low prevalence of eGFR could be due to (1) chance, (2) the artefact of differences in the serum creatinine measurement, (3) changes in serum creatinine production rather than excretion by the kidney, (4) residual confounding by differences in sample characteristics not adjusted for by sample weighting and (5) the true fall in eGFR.
So, the variables of each sample consisted of contents of peak 1, peak 6 and peak 7 and PA/W (peak area divided by sample weight) values of peak 2 ~ peak 5.
Principal component analysis (PCA), one of the popular chemometrics, was then used for comprehensive and systematic assessment on PMC samples collected from different regions with different diameters, based on the variables including the contents of the three quantified analytes and the PA/W (peak area divided by sample weight) values of the four unquantified ones.
Results in figures of IL-1 α, IL-6, IL-10, IL-12, PGE2, and TNF- α were calculated as follows: ELISA result (pg/mL) divided by sample weight in milligrams.
In our study, we quantified these two processes by measuring the sample weight and moisture and calculated the loss of dry solids.
Prevalence values were weighted by sample weights to provide population estimates.
Reported values were weighted by sample weights to provide population estimates.
It is strongly recommended always to correct by sample weights.
On the same reasoning, we strongly recommend always correcting by sample weights.
Using the ' svy' commands in Stata 12, overall animal-level seroprevalence was calculated by weighting each individual's result by its sampling weight and the standard error was adjusted for clustering and weighting.
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