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Nature article on reproducibility in science.

According to that article, a (surprisingly) large number of experiments aren't reproducible, or at least there have been failed attempted reproductions. In one of the figures, it's said that 70% of scientists in physics & engineering have failed to reproduce someone else's results, and 50% have failed to reproduce their own.

Clearly, if something cannot be reproduced, its veracity is called into question. Also clearly, because there's only one particle accelerator with the power of the LHC in the world, we aren't able to independently reproduce LHC results; in fact naively one might expect there's a 50% chance that if we built another LHC, it will not reach the same results. How, then, do we know that the LHC results (such as the discovery of the Higgs boson) are robust? Or do we not know the LHC results are robust, and are effectively proceeding on faith that they are?

That's a really great question. The 'replication crisis' is that many effects in social sciences couldn't be reproduced. There are many factors leading to this phenomenon, including

• Weak standards of evidence, e.g., $2sigma$ evidence required to demonstrate an effect


• Researchers (subconsciously or otherwise) conducting bad scientific practice by selectively reporting and publishing significant results. E.g. considering many different effects until they find a significant effect or collecting data until they find a significant effect.


• Poor training in statistical methods.

I'm not entirely sure about the exact efforts that the LHC experiments are making to ensure that they don't suffer the same problems. But let me say some things that should at least put your mind at ease:

• Particle physics typically requires a high-standard of evidence for discoveries ($5sigma$)


• The results at the LHC are already replicated!
  
  
  
  
  • There are several detectors placed around the LHC ring. Two them, called ATLAS and CMS, are general purpose detectors for Standard Model and Beyond the Standard Model physics. Both of them found compelling evidence for the Higgs boson.
  
  
  • The Tevatron, a similar collider experiment in the USA operating at lower-energies, found direct evidence for the Higgs boson.
  
  
  • The Higgs boson was observed several datasets collected at the LHC
  
  
  
  


• The LHC (typically) publishes findings regardless of their statistical significance, i.e., significant results are not selectively reported.


• The LHC teams are guided by statistical committees, hopefully ensuring good practice


• The LHC is in principle committed to open data, which means a lot of the data should at some point become public. This is one recommendation for helping the crisis in social sciences.


• Typical training for experimentalists at the LHC includes basic statistics (although in my experience LHC experimentalits are still subject to the same traps and misinterpretations as everyone else).


• All members (thousands) of the experimental teams are authors on the papers. The incentive for bad practices such as $p$-hacking is presumably slightly lowered, as you cannot 'discover' a new effect and publish it only under your own name, and have improved job/grant prospects. This incentive might be a factor in the replication crisis in social sciences.


• All papers are subject to internal review (which I understand to be quite rigorous) as well as external review by a journal


• LHC analyses are often (I'm not sure who plans or decides this) blinded. This means that the experimentalists cannot tweak the analyses depending on the result. They are 'blind' to the result, make their choices, then unblind it only at the end. This should help prevent $p$-hacking
  


• LHC analysis typically (though not always) report a global $p$-value, which has beeen corrected for multiple comparisons (the look-elsewhere effect).

If anything, there is a suspicion that the practices at the LHC might even result in the opposite of the 'replication crisis;' analyses that find effects that are somewhat significant might be examined and tweaked until they decrease.

This is an answer to the question above, as I do not have access to the paper I cannot really discuss it.

Here is a simpler example: Take an Olympics athlete. How many failures before breaking the record? Is the record not broken because there may have been a thousand failures before breaking it?

What about the hundreds of athletes who try to reproduce and get a better record? Should they not try?

The statistics of failed experiments is similar: There is a goal (actually thousands of goals depending on the physics discipline), and a number of trials to reach the goal.

We know the LHC results are robust because there are two major and many smaller experiments trying for the same goals. The reason there are two experiments is so that systematic errors in one will not give spurious results. We trust that the measurement statistics that give the end results are correct, as we trust for the record breaking run that the measured times and distances are correct.

(And LHC is not an experiment. It is where experiments can be carried out depending on the efforts and ingenuity of researchers, it is the field where the Olympics takes place.)

The robustness of scientific results depends on the specific experimental measurements, not on integrating over all disparate experiments ever made. Bad use of statistics in mixing up apples and oranges and cauliflower and then applying it to the stock market.

Another way to look at it: If there were no failures , would the experiments mean anything? They would be predictable by pen and paper.