Decline effect

The decline effect may occur when scientific claims receive decreasing support over time.

In the first example, the development of second generation anti-psychotic drugs, reveals that the first tests had demonstrated a dramatic decrease in the subjects' psychiatric symptoms.

In an initial series of studies Schooler found evidence that verbal rehearsal of previously seen faces or colors markedly impaired subsequent recognition.

Although verbal overshadowing effects have been repeatedly observed by Schooler, as well as other researchers, they have also proven to be somewhat challenging to replicate.

He has argued that addressing the decline effect may require a major revision to the scientific process whereby scientists log their protocols before conducting their research and then, regardless of outcome, report their findings in an open access repository (such as Brian Nosek's "Project Implicit").

[6] Schooler is currently working with the Fetzer Foundation to organize a major meeting of scientists from various disciplines to consider alternative accounts of the decline effect and approaches for rigorously addressing it.

[7] In 1991, Danish zoologist Anders Møller discovered a connection between symmetry and sexual preference of female birds in nature.

[10] For example, statistically significant phenomena in parapsychology are false positives, and so is facilitated communication.

Because less sick patients has less room for improvement, the effect size of Timolol decreased.

[10] This is a statistical phenomenon happening when a variable is extreme on the first experiments and by later experiments tend to regress towards average, although this does not explain why sequential results decline in a linear fashion, rather than fluctuating about the true mean as would be expected.

[2] As a result, the journals may refuse to publish papers that do not prove that the idea works.

[14] A significant factor contributing to the decline effect can also be the sample size of the scientific research, since smaller sample size is very likely to give more extreme results, suggesting a significant breakthrough, but also a higher probability of an error.

Typical examples of this effect are the opinion polls, where those including a larger number of people are closer to reality than those with a small pool of respondents.

Later, as larger studies are being made, they often show regression to the mean and a failure to repeat the early exaggerated results.

[16][17][18] A 2012 report by National Public Radio's show "On The Media"[19] covered scientists who are exploring another option: that the act of observing the universe changes the universe, and that repeated measurement might actually be rendering earlier results invalid.

Science fiction author Geoff Ryman explores this idea and its possible ramifications further in his 2012 short story What We Found,[20] which won the Nebula Award for Best Novelette in 2012.

[22] Several commenters have contested Jonah Lehrer's view of the decline effect being a problematic side of the phenomenon, as presented in his New Yorker article.

Novella points out that most of the examples used by Lehrer come from medicine, psychology and ecology, scientific fields most influenced by a complex human aspect and that there is not much evidence of the decline effect in other areas of science, such as physics.

"[24] Lehrer's statements about the difficulty of proving anything and publication bias find support from Jerry A. Coyne.

However, he also contests Lehrer's approach of applying conclusions on all fields of science, stating that in physics, chemistry or molecular biology, previous results are constantly repeated by others in order to progress in their own research.

[25] One concern that some [26] have expressed is that Lehrer's article may further fuel people's skepticism about academic science.

Lehrer ends the article by saying: "Just because an idea is true doesn't mean it can be proved.

[8] In this note, entitled "More Thoughts on the Decline Effect", Lehrer tries mainly to answer the critics by giving examples where scientific research has both failed and succeeded.

As an example, Lehrer uses Richard Feynman's commencement speech at Caltech in 1974 as a starting point.

In his commencement speech, Feynman used Robert Millikan's and Harvey Fletcher's oil drop experiment to measure the charge of an electron to illustrate how selective reporting can bias scientific results.

Instead, he wishes that "we'd spend more time considering the value of second-generation antipsychotics or the verity of the latest gene-association study".

In the other parts of the follow-up note, Lehrer briefly discusses some of the creative feedback he has received in order to reduce publication bias.

The decline effect in ocean acidification effects on fish behavior. The strength of effect declined by an order of magnitude over a decade of research on this topic. The decline effect in this field appears to be driven by publication bias , citation bas, sample sizes , and particular investigators publishing large effect sizes . [ 9 ]
Interaction between sample size, effect size, and statistical power. Distributions of sample means under the null (θ=0) and alternative hypotheses are shown. The shaded red area represents significance (α), held constant at 0.05, while the shaded green area represents statistical power (1-β). As the sample size increases, the distributions narrow, leading to clearer separation between the hypotheses and higher power. Similarly, a larger effect size increases the distance between the distributions, resulting in greater power.