An exploratory test for an excess of significant findings. Ioannidis, J. P A. & Trikalinos, T. A. Clin Trials, 4(3):245–253, 2007.
doi  abstract   bibtex   
The published clinical research literature may be distorted by the pursuit of statistically significant results.We aimed to develop a test to explore biases stemming from the pursuit of nominal statistical significance.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).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.The proposed test is exploratory, may depend on prior assumptions, and should be applied cautiously.An excess of significant findings may be documented in some clinical research fields.
@Article{Ioannidis2007,
  author      = {Ioannidis, John P A. and Trikalinos, Thomas A.},
  journal     = {Clin Trials},
  title       = {An exploratory test for an excess of significant findings.},
  year        = {2007},
  number      = {3},
  pages       = {245--253},
  volume      = {4},
  abstract    = {The published clinical research literature may be distorted by the
	pursuit of statistically significant results.We aimed to develop
	a test to explore biases stemming from the pursuit of nominal statistical
	significance.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).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.The proposed test is exploratory, may depend on prior
	assumptions, and should be applied cautiously.An excess of significant
	findings may be documented in some clinical research fields.},
  doi         = {10.1177/1740774507079441},
  institution = {Clinical 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},
  keywords    = {Antipsychotic Agents, therapeutic use; Bias (Epidemiology); Clinical Trials as Topic, methods/statistics /&/ numerical data; Data Interpretation, Statistical; Humans; Meta-Analysis as Topic; Probability; Schizophrenia, drug therapy},
  language    = {eng},
  medline-pst = {ppublish},
  pmid        = {17715249},
  timestamp   = {2015.07.19},
}

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