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The Benjamini and Hochberg method was selected to adjust P values for multiple testing [ 32].
Neither was the content selected to adjust and facilitate understanding by the students.
The variables selected to adjust the pathway were the ones with the highest associations in the previous analyses.
Also presented is the proportion of replicates of simulated data in which more than the first three axes of genetic variation were selected to adjust for population structure.
The Benjamini and Hochberg method was selected to adjust p-values for multiple testing and to determine false discovery rates (FDRs) [ 67].
A larger sample of 220 community pharmacies (out of a total of 287) was selected to adjust for possible nonresponse, using stratified and systematic random sampling according to the methodology described by World Health Organization [ 28].
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Conversely, users may select to adjust the survival model for available covariates for particular datasets, in which case selected covariates are added to the cox proportional hazards model with gene expression variable.
We selected covariates to adjust for possible confounding in the analyses (control variables) and to examine the potential of selected variables to modify associations between slum residency and infant mortality or child stunting (i.e., household wealth, maternal education, and antenatal care for infant mortality, with the addition of child age for stunting).
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We selected household income to adjust for SES in this study because its adjustment showed a larger impact on the ORs for the association between Tl and LBW than did the other two SES variables.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com