An exploratory test for an excess of significant findings

By John P. A. Ioannidis, Thomas A. Trikalinos. Clinical Trials, 2007

681 citations recorded by the source corpus.

Subfields: Pharmacology, Psychiatry and Mental health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2d8000c3b25b0707ed8c0c77d131ac84a5e814d1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Pharmacology

1. David Moher
2. Douglas G. Altman
3. T. Stanley
4. Hristos Doucouliagos
5. Annette van Dijk
6. Jelte M. Wicherts
7. Marjan Bakker
8. John P. A. Ioannidis

In Psychiatry and Mental health

1. T. Stanley
2. Annette van Dijk
3. Jelte M. Wicherts
4. Marjan Bakker
5. Hristos Doucouliagos
6. John P. A. Ioannidis

In Statistics and Probability

1. David Moher
2. Douglas G. Altman
3. John P. A. Ioannidis
4. J. Tetzlaff
5. Hristos Doucouliagos
6. K. F. Schulz
7. J. Polanin
8. Mike Clarke

Citations in the corpus

• Scientific Utopia: II. Restructuring Incentives and Practices to Promote Truth Over Publishability (2012, result): “…evidence for or against ideas suggested previously; (b) reporting positive results and ignoring negative results (Fanelli, 2012; Greenwald, 1975; Ioannidis & Trikalinos, 2007; Rosenthal, 1979); and (c) pursuing design, reporting, and analysis strategies that increase the likelihood of obtaining…”
• Systematic meta-analyses and field synopsis of genetic association studies in schizophrenia: the SzGene database (2008, neutral): “Therefore, we carried out an additional diagnostic test that aims to detect whether there was an excess of statistically significant single studie”
• The Rules of the Game Called Psychological Science (2012, methodology): “Ioannidis and Trikalinos (2007) proposed a straightforward χ2 test for such an excess of significant findings: χ2 (DF = 1) = 6.21, p = .013.”
• The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration (2009, background): “Several alternative tests for bias have also been proposed, beyond the ones testing small study bias [215,219,220], but none can be considered a gold standard.”
• The Power of Bias in Economics Research (2017, methodology): “…1979; Glass et al., 1981; Lovell, 1983; Hedges and Olkin, 1985; Begg and Berlin, 1988; De Long and Lang, 1992; Card and Krueger, 1995; Sterling et al., 1995; Copas, 1999; Ioannidis and Trikalinos, 2007; Stanley, 2008; Stanley and Doucouliagos, 2012, 2014; to cite but a few relevant references).”
• Why Most Discovered True Associations Are Inflated (2008, background): “Recently, a test was proposed to examine whether the number of reported study results that pass certain levels of statistical significance is reasonable or larger than what one would expect, even if the effect sizes for the proposed associations (eg, as suggested by meta-analyses of all relevant stu”