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2016 ; 11
(5
): e0153049
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Testing for Questionable Research Practices in a Meta-Analysis: An Example from
Experimental Parapsychology
#MMPMID27144889
Bierman DJ
; Spottiswoode JP
; Bijl A
PLoS One
2016[]; 11
(5
): e0153049
PMID27144889
show ga
We describe a method of quantifying the effect of Questionable Research Practices
(QRPs) on the results of meta-analyses. As an example we simulated a
meta-analysis of a controversial telepathy protocol to assess the extent to which
these experimental results could be explained by QRPs. Our simulations used the
same numbers of studies and trials as the original meta-analysis and the
frequencies with which various QRPs were applied in the simulated experiments
were based on surveys of experimental psychologists. Results of both the
meta-analysis and simulations were characterized by 4 metrics, two describing the
trial and mean experiment hit rates (HR) of around 31%, where 25% is expected by
chance, one the correlation between sample-size and hit-rate, and one the
complete P-value distribution of the database. A genetic algorithm optimized the
parameters describing the QRPs, and the fitness of the simulated meta-analysis
was defined as the sum of the squares of Z-scores for the 4 metrics. Assuming no
anomalous effect a good fit to the empirical meta-analysis was found only by
using QRPs with unrealistic parameter-values. Restricting the parameter space to
ranges observed in studies of QRP occurrence, under the untested assumption that
parapsychologists use comparable QRPs, the fit to the published Ganzfeld
meta-analysis with no anomalous effect was poor. We allowed for a real anomalous
effect, be it unidentified QRPs or a paranormal effect, where the HR ranged from
25% (chance) to 31%. With an anomalous HR of 27% the fitness became F = 1.8 (p =
0.47 where F = 0 is a perfect fit). We conclude that the very significant
probability cited by the Ganzfeld meta-analysis is likely inflated by QRPs,
though results are still significant (p = 0.003) with QRPs. Our study
demonstrates that quantitative simulations of QRPs can assess their impact. Since
meta-analyses in general might be polluted by QRPs, this method has wide
applicability outside the domain of experimental parapsychology.