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Olavo B. Amaral
Reunião de Editores Científicos
CRICS10
Dezembro 2018
Research reproducibility
and scientific publication
• We are used to hearing that scientific articles are the most
reliable source of evidence to which we have access.
• That said, we have surprisingly little empirical evidence for
this claim.
An established paradigm
Some numbers...
Some numbers...
Some numbers...
Some numbers...
Some numbers...
• 11 published studies:
- 4 mostly replicated
- 3 partially replicated
- 2 non-replicated
- 2 not interpretable
Some numbers
An empirical conclusion...
• In the few areas of biomedical science studied, we cannot
presume that most published findings are true.
The rotten apple fallacy
• Retractions for misconduct have become more common,
but their frequency does not begin to explain the problem.
The standardization fallacy
• An opposite approach is to try to explain irreproducibility by
purely methodological questions that can’t be controlled
across laboratories.
(that said...)
Hell is in the grey zone
• The most useful way to
approach irreproducibility
is to look at the grey zone
between methodological
diffficulties and
misconduct.
Chance and bias
• With loose statistical standards, the sum of our biases can
easily turn chance into scientific ‘truth’.
The tragedy of p < 0.05
• The definition of ‘significance’ used by most life scientists
means that, with enough data and ways to analyze it, one can
prove basically anything.
• With sufficient experiments, ‘significant’ results will occur in
1 out of 20 experiments by definition, even if nothing is true.
• Analyzing the same experiment in 20 different ways, it is
usually not hard to find a ‘significant’ result either.
Publication/
Reporting Bias
A basic flaw
Replication
Citations
Impact
Changed plans
Data exploration
Analysis options
Obstacles
Negative results
Failed experiments
Criticism
• When reading a scientific article, we do not know the
original hypotheses, the number of comparisons and the
number of analysis options.
Like a Tinder profile
• This is not all that different from other ‘non-scientific’
syntheses of reality.
Replication
Citations
Impact
Changed plans
Data exploration
Analysis options
Obstacles
Negative results
Failed experiments
Criticism
Unmasking ‘impact’
• Traditional peer review conflates the evaluation of methods
and results (and of data and stories).
• Beautiful stories with lots of shaky data tend to trump solid,
well-performed experiments.
Volume
Novelty/Impact
- Number of
experiments,
methods, etc.
- Coherence of results
- Novelty of theory
- Potential impact
Rigor/Reproducibility
- Experimental design
- Protocol registration
- Data availability
- Statistical rigor
Doomed to fail
• Irreproducibility is the natural outcome in a system in which
impact and novelty count but truth does not.
Wrong time, wrong place
• Even when peer review does work, it comes at the wrong
time (after results are in) and behind closed doors.
Registered Reports
The death of prepublication peer review?
• It is time to discuss whether prepublication peer review
should not give way to different forms of quality control.
Time to experiment
• Do we lose that much by giving up on prepublication peer
review?
Score(%applicableitems)
bioRxiv PubMed
0
20
40
60
80
100
Quality of reporting of methods/results in
preprints vs. peer-reviewed articles
bioRxiv 59.4% vs. 63.9% PubMed
p = 0.019, r2 = 0.036
Carneiro et al., in prep.
https://osf.io/rxqn4/
Actual peer review
• We urgently need better data on reproducibility in various
scientific environments.
• 71 lab-strong initiative to reproduce 50-100 experiments from
Brazilian life sciences articles over the last 20 years.
• Each experiment reproduced in 3 labs to estimate interlab
variability.
• http://reprodutibilidade.bio.br
No need to fear change
• Unlike with democracy, we have not really tried out anything
different for the last century.
Barriers are cultural, not scientific
• Peer review has become more important for science as a form
of branding than of actual quality control.
Conclusions
• The current model of article peer review as a barrier to
publication based is more harmful than helpful for science.
• Changing the way we publish science to make it more
reproducible and accessible is an ethical imperative.
• These changes must be accompanied by changes in how we
evaluate science.
• The barriers to change are cultural rather than financial or
technological.
The tide is changing
• It is time to decide whether to cling to a sinking ship or to
help building new ones.
• http://asapbio.org
Come aboard!
http://reprodutibilidade.bio.br
@reprodutibilidade.bio.br
reprodutibilidade.br@gmail.com
http://osf.io/6av7k/
@BrRepInitiative
olavo@bioqmed.ufrj.br

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Reprodutibilidade em resultados de pesquisa (Olavo Bohrer Amaral)

  • 1. Olavo B. Amaral Reunião de Editores Científicos CRICS10 Dezembro 2018 Research reproducibility and scientific publication
  • 2. • We are used to hearing that scientific articles are the most reliable source of evidence to which we have access. • That said, we have surprisingly little empirical evidence for this claim. An established paradigm
  • 8. • 11 published studies: - 4 mostly replicated - 3 partially replicated - 2 non-replicated - 2 not interpretable Some numbers
  • 9. An empirical conclusion... • In the few areas of biomedical science studied, we cannot presume that most published findings are true.
  • 10. The rotten apple fallacy • Retractions for misconduct have become more common, but their frequency does not begin to explain the problem.
  • 11. The standardization fallacy • An opposite approach is to try to explain irreproducibility by purely methodological questions that can’t be controlled across laboratories. (that said...)
  • 12. Hell is in the grey zone • The most useful way to approach irreproducibility is to look at the grey zone between methodological diffficulties and misconduct.
  • 13. Chance and bias • With loose statistical standards, the sum of our biases can easily turn chance into scientific ‘truth’.
  • 14. The tragedy of p < 0.05 • The definition of ‘significance’ used by most life scientists means that, with enough data and ways to analyze it, one can prove basically anything.
  • 15. • With sufficient experiments, ‘significant’ results will occur in 1 out of 20 experiments by definition, even if nothing is true.
  • 16. • Analyzing the same experiment in 20 different ways, it is usually not hard to find a ‘significant’ result either.
  • 18. A basic flaw Replication Citations Impact Changed plans Data exploration Analysis options Obstacles Negative results Failed experiments Criticism • When reading a scientific article, we do not know the original hypotheses, the number of comparisons and the number of analysis options.
  • 19. Like a Tinder profile • This is not all that different from other ‘non-scientific’ syntheses of reality. Replication Citations Impact Changed plans Data exploration Analysis options Obstacles Negative results Failed experiments Criticism
  • 20. Unmasking ‘impact’ • Traditional peer review conflates the evaluation of methods and results (and of data and stories). • Beautiful stories with lots of shaky data tend to trump solid, well-performed experiments. Volume Novelty/Impact - Number of experiments, methods, etc. - Coherence of results - Novelty of theory - Potential impact Rigor/Reproducibility - Experimental design - Protocol registration - Data availability - Statistical rigor
  • 21. Doomed to fail • Irreproducibility is the natural outcome in a system in which impact and novelty count but truth does not.
  • 22. Wrong time, wrong place • Even when peer review does work, it comes at the wrong time (after results are in) and behind closed doors. Registered Reports
  • 23. The death of prepublication peer review? • It is time to discuss whether prepublication peer review should not give way to different forms of quality control.
  • 24. Time to experiment • Do we lose that much by giving up on prepublication peer review? Score(%applicableitems) bioRxiv PubMed 0 20 40 60 80 100 Quality of reporting of methods/results in preprints vs. peer-reviewed articles bioRxiv 59.4% vs. 63.9% PubMed p = 0.019, r2 = 0.036 Carneiro et al., in prep. https://osf.io/rxqn4/
  • 25. Actual peer review • We urgently need better data on reproducibility in various scientific environments. • 71 lab-strong initiative to reproduce 50-100 experiments from Brazilian life sciences articles over the last 20 years. • Each experiment reproduced in 3 labs to estimate interlab variability. • http://reprodutibilidade.bio.br
  • 26. No need to fear change • Unlike with democracy, we have not really tried out anything different for the last century.
  • 27. Barriers are cultural, not scientific • Peer review has become more important for science as a form of branding than of actual quality control.
  • 28. Conclusions • The current model of article peer review as a barrier to publication based is more harmful than helpful for science. • Changing the way we publish science to make it more reproducible and accessible is an ethical imperative. • These changes must be accompanied by changes in how we evaluate science. • The barriers to change are cultural rather than financial or technological.
  • 29. The tide is changing • It is time to decide whether to cling to a sinking ship or to help building new ones. • http://asapbio.org