The AUTHORS of the original paper got a dataset from a company. They didn't assume the fraud from the start and published the paper based on it.
Later, when they tried to analyze the issue more in-depth, they couldn't replicate the results. THE ORIGINAL AUTHORS PUBLISHED a paper about a failure to replicate. It was just then that someone looked at the original data and found that it was faked.
I did completely read what was available to me without having an account.
> The AUTHORS of the original paper got a dataset from a company. They didn't assume the fraud from the start and published the paper based on it.
My comment is not about who the culprit is or isn't. Indeed, I don't mention anything about it.
Rather, it's about how, as the title says, a WIDELY cited paper has fabricated data following rather (IMO) obvious red flag patterns and none of the people -who cited the paper- raised issues about that.
Thus, I questioned whether scientists read or not the papers they cite in the parent post.
The question is not a judgment, I'm just truly curious since I'm not part of the formal academia, just an undergraduate.
He created the excel file. If he wanted to clear his name he could publish the original data as it was sent from the company, but he hasn't done so. And the company obviously has no incentive to falsify the data.
If they did a good job hiding it then you wouldn't know about it. For every case like this where they made a obvious mistake, there are cases where they didn't, and nobody noticed. But you only tend to hear about the ones with obvious mistakes.
No. What are you kidding me. There's like typically over 50 papers referenced in a typical publication, no way I have the time to read all of them carefully
Yes, but few actually scrutinize the methodology of the studies. Statistics is really hard. It's easier to assume peer reviewers would have rejected the paper if it was bad.
Benford's law (https://en.wikipedia.org/wiki/Benford%27s_law) is a pretty well-known test for fraudulent numbers. Of course, it's not infallible and (depending on the nature of the fake) it may be possible to tailor the numbers to 'pass' it, but it's a good heuristic. I'd be curious to know whether it would have detected this - and, if so, whether it was indeed used.
I depends on ones probity, but yes the phenomenon is widespread. There are numerous reasons to cite a paper and just read it superficially: padding the references list, pleasing a reviewer by adding a paper he recommended, citing friends, etc. In my own lab they frequently cite a certain theory which if you actually read about it has nothing to do with what they are doing.
The problem is often that reading it is insufficient. Unless you try to replicate, it may well look plausible, and often missing data or details creates barriers that makes you need to want to replicate really badly to put in the effort.
The AUTHORS of the original paper got a dataset from a company. They didn't assume the fraud from the start and published the paper based on it.
Later, when they tried to analyze the issue more in-depth, they couldn't replicate the results. THE ORIGINAL AUTHORS PUBLISHED a paper about a failure to replicate. It was just then that someone looked at the original data and found that it was faked.