P-values are so weird. Studies should instead report a likelihood ratio. A likelihood ratio is mathematically correct, and tells you exactly how much to update

P-values are so weird. Studies should instead report a likelihood ratio. A likelihood ratio is mathematically correct, and tells you exactly how much to update a hypothesis. You can convert p-values to likelihood ratios, and they are quite similar. But its not perfect. A p value of 0.05 becomes 100:5, or 20:1. Which means it increases the odds of a hypothesis by 20. So a probability of 1% updates to 17%, which is still quite small. But that assumes that the hypothesis has a 100% chance of producing the same or greater result, which is unlikely. Instead it might only be 50% which is half as much evidence. In the extreme case, it could be only 5% likely to produce the result, which means the likelihood ratio is 5:5 and is literally no evidence, but still has a p value of 0.05. Anyway likelihood ratios accumulate exponentially, since they multiply together. As long as there is no publication bias, you can take a few weak studies and produce a single very strong likelihood update.