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The decline effect and the scientific method : The New Yorker

m.newyorker.com
The disturbing implication of the Crabbe study is that a lot of extraordinary scientific data are nothing but noise.
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 196-197 | Added on Monday, 22 July 13 19:04:35
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Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. ?I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,? Schooler says. ?It would help us finally deal with all these issues that the decline effect is exposing.?
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 178-181 | Added on Monday, 22 July 13 19:04:01
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Schooler argues that scientists need to become more rigorous about data collection before they publish. ?We?re wasting too much time chasing after bad studies and underpowered experiments,? he says. The current ?obsession? with replicability distracts from the real problem, which is faulty design. He notes that nobody even tries to replicate most science papers?there are simply too many. (According to Nature, a third of all studies never even get cited, let alone repeated.) ?I?ve learned the hard way to be exceedingly careful,? Schooler says. ?Every researcher should have to spell out, in advance, how many subjects they?re going to use, and what exactly they?re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.?
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 172-178 | Added on Monday, 22 July 13 19:03:48
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Richard Palmer, a biologist at the University of Alberta, who has studied the problems surrounding fluctuating asymmetry, suspects that an equally significant issue is the selective reporting of results?the data that scientists choose to document in the first place. Palmer?s most convincing evidence relies on a statistical tool known as a funnel graph. When a large number of studies have been done on a single subject, the data should follow a pattern: studies with a large sample size should all cluster around a common value?the true result?whereas those with a smaller sample size should exhibit a random scattering, since they?re subject to greater sampling error. This pattern gives the graph its name, since the distribution resembles a funnel. The funnel graph visually captures the distortions of selective reporting. For instance, after Palmer plotted every study of fluctuating asymmetry, he noticed that the distribution of results with smaller sample sizes wasn?t random at all but instead skewed heavily toward positive results. Palmer has since documented a similar problem in several other contested subject areas. ?Once I realized that selective reporting is everywhere in science, I got quite depressed,? Palmer told me. ?As a researcher, you?re always aware that there might be some nonrandom patterns, but I had no idea how widespread it is.? In a recent review article, Palmer summarized the impact of selective reporting on his field: ?We cannot escape the troubling conclusion that some?perhaps many?cherished generalities are at best exaggerated in their biological significance and at worst a collective illusion nurtured by strong a-priori beliefs often repeated.?
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 125-136 | Added on Monday, 22 July 13 19:01:07
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The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for.
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 115-116 | Added on Monday, 22 July 13 18:59:32
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The most likely explanation for the decline is an obvious one: regression to the mean. As the experiment is repeated, that is, an early statistical fluke gets cancelled out. The extrasensory powers of Schooler?s subjects didn?t decline?they were simply an illusion that vanished over time. And yet Schooler has noticed that many of the data sets that end up declining seem statistically solid?that is, they contain enough data that any regression to the mean shouldn?t be dramatic. ?These are the results that pass all the tests,? he says. ?The odds of them being random are typically quite remote, like one in a million. This means that the decline effect should almost never happen. But it happens all the time! Hell, it?s happened to me multiple times.? And this is why Schooler believes that the decline effect deserves more attention: its ubiquity seems to violate the laws of statistics.
The decline effect and the scientific method : The New Yorker - m.newyorker.com - Your Highlight Location 73-79 | Added on Monday, 22 July 13 18:56:15
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