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Leek summarized the key points of agreement as: when talking about the science-wise false discovery rate one has to bring data; there are different frameworks for estimating the science-wise false discovery rate; and "it is pretty unlikely that most published research is false", but that probably varies by one's definition of "most" and "false".
The following statements are examples of false equivalence: [3] "The Deepwater Horizon oil spill is no more harmful than when your neighbor drips some oil on the ground when changing his car's oil." The "false equivalence" is the comparison between things differing by many orders of magnitude: [ 3 ] Deepwater Horizon spilled 210 million US gal ...
Exploring a forking decision-tree while analyzing data was at one point grouped with the multiple comparisons problem as an example of poor statistical method. However Gelman and Loken demonstrated [2] that this can happen implicitly by researchers aware of best practices who only make a single comparison and only evaluate their data once.
In Denmark, scientific misconduct is defined as "intention[al] negligence leading to fabrication of the scientific message or a false credit or emphasis given to a scientist", and in Sweden as "intention[al] distortion of the research process by fabrication of data, text, hypothesis, or methods from another researcher's manuscript form or ...
Publication of studies on p-hacking and questionable research practices: Since the late 2000s, a number of studies in metascience showed how commonly adopted practices in many scientific fields, such as exploiting the flexibility of the process of data collection and reporting, could greatly increase the probability of false positive results.
A 2003 study by the Hungarian Academy of Sciences found that 70% of articles in a random sample of publications about least-developed countries did not include a local research co-author. [ 37 ] Frequently, during this kind of research, the local colleagues might be used to provide logistics support as fixers but are not engaged for their ...
In both examples, as the number of comparisons increases, it becomes more likely that the groups being compared will appear to differ in terms of at least one attribute. Our confidence that a result will generalize to independent data should generally be weaker if it is observed as part of an analysis that involves multiple comparisons, rather ...
FWER control limits the probability of at least one false discovery, whereas FDR control limits (in a loose sense) the expected proportion of false discoveries. Thus, FDR procedures have greater power at the cost of increased rates of type I errors, i.e., rejecting null hypotheses that are actually true.