Detecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach.

ABSTRACT:

Background

The randomized controlled study is the gold-standard research method in biomedicine. In contrast, the validity of a (nonrandomized) observational study is often questioned because of unknown/unmeasured factors, which may have confounding and/or effect-modifying potential.

Methods

In this paper, the author proposes a perturbation test to detect the bias of unmeasured factors and a perturbation adjustment to correct for such bias. The proposed method circumvents the problem of measuring unknowns by collecting the perturbations of unmeasured factors instead. Specifically, a perturbation is a variable that is readily available (or can be measured easily) and is potentially associated, though perhaps only very weakly, with unmeasured factors. The author conducted exten

SUBMITTER: Lee WC 

PROVIDER: S-EPMC3925987 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature