being sceptical
What do we know? – in conclusion • How do you know that? Should always ask • Source – what is the source of info? • Quality of the evidence • Control groups?
The publication process
The publication process
o But all studies have their drawbacks. Methodological issues, sampling issues etc
o Their conclusions may be limited in scope
o Each article builds on a body of knowledge, that when taken as a whole is useful.
• The publication process is also a human endeavour
o The Scientist
o The Reviewers
o The Editing Team
o The journal and the type of articles it “accepts”
Where to submit
Who picks it up?
What is their bias?
Which people do they ‘know’ that might review
this given their knowledge of the literature?
The publication process
Blind reviews? - Maybe not. People tend to cite themselves, so sometimes very obvious - Might even say “we have previously shown that….. (Guest & Lamberts, 2011)”
Reviewers are also often not named – imagine a long form academic version of twitter, pre-twitter.
(see examples that follow)
What are the reviewers biases? Do they have a competing theory? Do they agree? Does this work confirm/extend their findings?
What are the incentives for academics?
Neuroskeptic (2012) The Nice Circles of Scientific Hell
Problems in the publication method
• The article raises a variety of issues – most of these impact the ability to replicate findings – which is hugely problematic, as science can only develop IF findings have a decent degree of replicability
• Issues raised;
• Turning a blind eye.
• Exaggeration
o Often in psychology – papers find “significant” results, but actually the size of these effects might be small
o Motivated to do so to make a bigger splash and get published
Post hoc story telling
• Science is about developing and testing hypothesis. If the hypotheses come after the data…
P value fishing
• You should make a hypotheses and run the test that best tests this. If you run lots of tests of different kinds, then statistically you are likely to find something significant simply by chance alone …
Outliers
• Outliers are a significant problem in data analysis. If you have extreme scores they can seriously mess up things like means and standard deviations, which are things that are used in many statistical tests.
• So you need them out. But that means selecting what is an outlier based on a rule and sticking to that.
• E.g., in some of my tests RTs < 300ms are impossible and
RTs> 2000ms are very slow indeed and suggest someone has not done that particular trial.
• But removing can influence analysis – so say whether it does!
Non publication of data
Partial publication
• Conduct a large study in which lots of things are measured, but then publish different papers only on sub-sets of this overall data.
replication
Studies focused just on replication used to be relatively rare because: