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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.
Presented principles and methods are illustrated through application to a small, wide data set of adults spanning a wide range in ages and multiple immunophenotypes that were assayed before and after immunization with inactivated influenza vaccine (IIV).
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Small, wide data sets are commonplace in human immunophenotyping research.
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.
Comparative studies of genome wide data sets are entirely dependent on the choice of common denominator for annotation [ 40].
Mining the numerous genome wide data sets related to protein function to retrieve potential candidate genes for a particular biological process remains a challenge.
It used a wider data set from the national pupil database of students who sat GCSEs between 2001 and 2008 and then followed their university career.
For this data set, we eliminated surveys in the same manner as done for the university-wide data set for a total of 487.
The total number of surveys used in the final university-wide data set was 2,999 – a response rate of 16.67%.
We added only the post course surveys (n = 154) to the data collected by the first two methods for the university-wide data set since all surveys were anonymous and we did not want to include duplicate responses.
That wider data set allows users to actually perform different commands with different thoughts.
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