Multivariate analysis of the population representativeness of related clinical studies.

ABSTRACT:

Objective

To develop a multivariate method for quantifying the population representativeness across related clinical studies and a computational method for identifying and characterizing underrepresented subgroups in clinical studies.

Methods

We extended a published metric named Generalizability Index for Study Traits (GIST) to include multiple study traits for quantifying the population representativeness of a set of related studies by assuming the independence and equal importance among all study traits. On this basis, we compared the effectiveness of GIST and multivariate GIST (mGIST) qualitatively. We further developed an algorithm called "Multivariate Underrepresented Subgroup Identification" (MAGIC) for constructing optimal combinations of distinct value intervals of m

SUBMITTER: He Z 

PROVIDER: S-EPMC4837055 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature