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SUMMARY:Circularity and selection bias in neuroscience and beyond: double 
 dipping\, publication bias\, and the decline of significant effects - Niko
  Kriegeskorte (MRC CBSU)
DTSTART:20131202T160000Z
DTEND:20131202T173000Z
UID:TALK46724@talks.cam.ac.uk
CONTACT:Mandy Carter
DESCRIPTION:A neuroscientific experiment typically generates a large amoun
 t of data\, of which only a small fraction is analyzed in detail and prese
 nted in a publication. However\, selection among noisy measurements can re
 nder circular an otherwise appropriate analysis and invalidate results. Sy
 stems neuroscience needs to adjust some widespread practices to avoid the 
 circularity that can arise from selection. In particular\, ‘double dippi
 ng’\, the use of the same dataset for selection and selective analysis\,
  will give distorted descriptive statistics and invalid statistical infere
 nce whenever the results statistics are not inherently independent of the 
 selection criteria under the null hypothesis. To demonstrate the problem\,
  we can apply widely used analyses to noise data known to not contain the 
 experimental effects in question. Spurious effects can appear in the conte
 xt of both univariate activation analysis and multivariate pattern-informa
 tion analysis. I will explain how circularity can be safely avoided in neu
 roimaging experiments. In the last 15 minutes\, I will broaden the scope b
 eyond neuroscience and discuss how selection at the level of studies and p
 ublications can introduce spurious results into the literature and create 
 biases affecting entire fields of science.
LOCATION:Seminar Room\, Department of Psychology\, Downing Site\, Cambridg
 e
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