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It is shown analytically that (1) the weighted version always improves the Pitman efficiency for all distributions; and (2) the optimal design is to select the median from each ranked set.
Finally, the distribution of log2 ratios in each group was standardized by subtracting the group's median from each log2 ratio, and then dividing by the group's median absolute deviation.
For data comparison, the background-subtracted signal intensity was normalized using global normalization in which the median from each microarray was used.
The standardization was performed subtracting the country global median from each individual score and then dividing the difference by the country inter-quartile range.
For each feature, data were normalized to reads per kilobase per million input reads and a range around the median from each stringency mapping was used to determine single coverage for that stringency.
Variability between plates was addressed by subtracting the plate median from each measurement per siRNA and dividing by the plate median absolute deviation (1σ) resulting in one z-score per siRNA per LabTek.
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The signal intensity medians from each spot were adjusted subtracting the local background intensity medians.
Comparison of median ages from each centre's study cohort suggested unequal medians (Kruskal-Wallis test, P < 0.001).
Here we compared each sample to the median sample for that data set under the assumption that the median patient from each data set would be similar.
For assessing liver function test abnormalities, the median values from each case series were calculated, and the range of these medians, rounded to the nearest 50 U/L, were reported.
Summary medians and standard deviations were calculated based on the reported or estimated median values from each individual study.
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