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Data were analyzed using the random-effects model and summarized using the Hedges's g.
The probesets were then normalized and summarized using the Robust Multichip Average method RMA [37].
Microarray data were normalized, background corrected and summarized using the robust multi-array average (RMA2) method [35].
The scanner-estimated background was subtracted from the Cy3 and Cy5 data for each ToxArray chip and the printed chips in the platform comparison study, and the logarithmic ratios were stabilized using the LOWESS function [16] in R. The GeneChip data were normalized and summarized using the MAS5 function or the RMA [15] function of affy [21].
First, all microarray data were normalized and summarized using the RMA algorithm.
The signal intensity of the microarray was normalized and summarized using the Bioconductor package, gcrma [ 26].
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Metabolite levels below the LOD were treated as 0.5 LOD for the purpose of statistical analysis and were summarized using the geometric mean, geometric SD, and percentiles.
The probe signal levels were quantile-normalized and then summarized using the RMA algorithm [ 69].
Comorbid diseases before the diagnosis/index date were identified using the hospital discharge registries of each county and were summarized using the Charlson Index [ 74].
The prevalence of wasting, stunting and underweight was summarized using the overall number and percent of children with each outcome by arm.
After staining and washing, arrays were scanned and expression values summarized using the MAS5 algorithm as implemented in the GCOS v1.4 software (Affymetrix, Santa Clara, CA).
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