Human immunophenotyping via low-variance, low-bias, interpretive regression modeling of small, wide data sets: Application to aging and immune response to influenza vaccination.
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ABSTRACT:
SUBMITTER: Holmes TH
PROVIDER: S-EPMC5242332 | biostudies-literature | 2016 Oct
REPOSITORIES: biostudies-literature
Publications
Human immunophenotyping via low-variance, low-bias, interpretive regression modeling of small, wide data sets: Application to aging and immune response to influenza vaccination.
Holmes Tyson H TH He Xiao-Song XS
Journal of immunological methods 20160516
Small, wide data sets are commonplace in human immunophenotyping research. As defined here, a small, wide data set is constructed by sampling a small to modest quantity n,1<n<50, of human participants for the purpose of estimating many parameters p, such that n<p<1000. We offer a set of prescriptions that are designed to facilitate low-variance (i.e. stable), low-bias, interpretive regression modeling of small, wide data sets. These prescriptions are distinctive in their especially heavy emphasi ...[more]
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