Do we know what proportion of scientific reproducibility issues are fraud-related? A few days ago there was an article on the LSE blog about scientific reproducibility which made little sense to me until I realised they were equating 'low reproducibility' with 'scientific fraud':

http://blogs.lse.ac.uk/impactofsocialsciences/2016/07/21/could-blockchain-provide-the-technical-fix-to-solve-sciences-reproducibility-crisis/

I've tended to assume that most reproducibility issues are poor reporting of experiments, poor recording of external factors, poor statistical analysis inflating p-values etc but I realise that I don't have much evidence to back that up apart from personal experience. Are there any studies that report the relative proportion of irreproducible experimental results resulting from fraud versus poor experimental/statistical/reporting standards?
I very much doubt we "know' this in the empirical sense, as:


As a scientific problem, the "reproducibility crisis" is fairly new, and we're still developing the methods to really understand it.
It's very hard to distinguish fraud from error except in the most egregious cases. You can say, for example, that there's clearly some bias in a body of work in a field, but it's hard to say that any particular paper is clearly biased.


For example, is a convergence error that you chose to ignore because it was "pretty close" to the convergence criteria you set for a statistical model an error, or fraud? How about using Bayesian priors that turn out to be stronger than was probably justified? How do you distinguish fraud in the form of "nudging" a result over the line into significance from a largely insignificant effect being estimated with error that sometimes crosses the null.

Frankly, there's not even, IMO, a solid definition of "irreproducible". Is that "Finds a statistically significant result"? "Effect estimates are on the same side of the null"? "Our clinical/policy conclusions would be the same"?

Lacking even that, I'd assert it would be particularly difficult to attempt to assess fraud vs. error in any systematic fashion.

It would also be an exceedingly difficult study to run, as you'd need the cooperation of a bunch of people who comitted fraud.