Evaluation of Excess Significance Bias in Animal Studies of Neurological Diseases

Konstantinos K Tsilidis, Orestis A Panagiotou, Emily S Sena, Eleni Aretouli, Evangelos Evangelou, David W Howells, Rustam Al-Shahi Salman, Malcolm R Macleod and John P A Ioannidis

PLOS Biology, 2013, vol. 11, issue 7, 1-10

Abstract: : The evaluation of 160 meta-analyses of animal studies on potential treatments for neurological disorders reveals that the number of statistically significant results was too large to be true, suggesting biases. Animal studies generate valuable hypotheses that lead to the conduct of preventive or therapeutic clinical trials. We assessed whether there is evidence for excess statistical significance in results of animal studies on neurological disorders, suggesting biases. We used data from meta-analyses of interventions deposited in Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies (CAMARADES). The number of observed studies with statistically significant results (O) was compared with the expected number (E), based on the statistical power of each study under different assumptions for the plausible effect size. We assessed 4,445 datasets synthesized in 160 meta-analyses on Alzheimer disease (n = 2), experimental autoimmune encephalomyelitis (n = 34), focal ischemia (n = 16), intracerebral hemorrhage (n = 61), Parkinson disease (n = 45), and spinal cord injury (n = 2). 112 meta-analyses (70%) found nominally (p≤0.05) statistically significant summary fixed effects. Assuming the effect size in the most precise study to be a plausible effect, 919 out of 4,445 nominally significant results were expected versus 1,719 observed (p

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pbio00:1001609

DOI: 10.1371/journal.pbio.1001609

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