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Clin Trials. 2007;4(3):245-53.

An exploratory test for an excess of significant findings.

Author information

  • 1Clinical Trials and Evidence Based Medicine Unit and Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece. jioannid@cc.uoi.gr

Abstract

BACKGROUND:

The published clinical research literature may be distorted by the pursuit of statistically significant results.

PURPOSE:

We aimed to develop a test to explore biases stemming from the pursuit of nominal statistical significance.

METHODS:

The exploratory test evaluates whether there is a relative excess of formally significant findings in the published literature due to any reason (e.g., publication bias, selective analyses and outcome reporting, or fabricated data). The number of expected studies with statistically significant results is estimated and compared against the number of observed significant studies. The main application uses alpha = 0.05, but a range of alpha thresholds is also examined. Different values or prior distributions of the effect size are assumed. Given the typically low power (few studies per research question), the test may be best applied across domains of many meta-analyses that share common characteristics (interventions, outcomes, study populations, research environment).

RESULTS:

We evaluated illustratively eight meta-analyses of clinical trials with >50 studies each and 10 meta-analyses of clinical efficacy for neuroleptic agents in schizophrenia; the 10 meta-analyses were also examined as a composite domain. Different results were obtained against commonly used tests of publication bias. We demonstrated a clear or possible excess of significant studies in 6 of 8 large meta-analyses and in the wide domain of neuroleptic treatments.

LIMITATIONS:

The proposed test is exploratory, may depend on prior assumptions, and should be applied cautiously.

CONCLUSIONS:

An excess of significant findings may be documented in some clinical research fields.

Comment in

PMID:
17715249
[PubMed - indexed for MEDLINE]
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