Do simple screening statistical tools help to detect reporting bias?

ABSTRACT:

Background

As a result of reporting bias, or frauds, false or misunderstood findings may represent the majority of published research claims. This article provides simple methods that might help to appraise the quality of the reporting of randomized, controlled trials (RCT).

Methods

This evaluation roadmap proposed herein relies on four steps: evaluation of the distribution of the reported variables; evaluation of the distribution of the reported p values; data simulation using parametric bootstrap and explicit computation of the p values. Such an approach was illustrated using published data from a retracted RCT comparing a hydroxyethyl starch versus albumin-based priming for cardiopulmonary bypass.

Results

Despite obvious nonnormal distributions, several variables a

SUBMITTER: Pirracchio R 

PROVIDER: S-EPMC3847052 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature