“Why Most Published Research Findings Are False”

[GordMay]

“Why Most Published Research Findings Are False” ~ by John P. A. Ioannidis
“There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research...”
Article ➥ https://journals.plos.org/plosmedici...l.pmed.0020124

Note: This article didn't go unchallenged. See "Related PLOS Articles", to the right of the main article.

[GordMay]

“Scientists rise up against statistical significance”
Valentin Amrhein, Sander Greenland, Blake McShane and more than 800 signatories call for an end to hyped claims and the dismissal of possibly crucial effects.
“... For several generations, researchers have been warned that a statistically non-significant result does not ‘prove’ the null hypothesis (the hypothesis that there is no difference between groups or no effect of a treatment on some measured outcome)1. Nor do statistically significant results ‘prove’ some other hypothesis. Such misconceptions have famously warped the literature with overstated claims and, less famously, led to claims of conflicts between studies where none exists.
We have some proposals to keep scientists from falling prey to these misconceptions ...”
Article ➥ https://www.nature.com/articles/d41586-019-00857-9

“It’s time to talk about ditching statistical significance”
➥ https://www.nature.com/articles/d41586-019-00874-8

“Five ways to fix statistics”
➥ https://www.nature.com/articles/d41586-017-07522-z

[UFO]

"There are three kinds of lies: lies, damned lies, and statistics."

[boatman61]

Whoda thunk it..

[Suijin]

So by extension this research finding has a high statistical probability of being false lolz

[bill352]

Originally Posted by Suijin

So by extension this research finding has a high statistical probability of being false lolz

[GordMay]

Originally Posted by Suijin

So by extension this research finding has a high statistical probability of being false lolz

Indeed; one of the exact points Dr. Wren brings up, in the following paper.


“Truth, Probability, and Frameworks” ~ by Jonathan D Wren
“... Although John P. A. Ioannidis [1] brings up several good points about over-reliance on formal—yet arbitrary—statistical cutoffs and bias against the reporting of negative results, his claim that most published research findings are false is somewhat paradoxical. Ironically, the truer his premise is, the less likely his conclusions are. He, after all, relies heavily on other studies to support his premise, so if most (i.e., greater than 50%) of his cited studies are themselves false (including the eight of 37 that pertain to his own work), then his argument is automatically on shaky ground ...”
➥ https://journals.plos.org/plosmedici...l.pmed.0020361

[john61ct]

Smells like continued attacks on the fundamental concept that we all share one Reality

about which Science has objectively True things to say.

I completely concede that this is worth challenging philosophically.

But wrt driving government policy and our day to day decisions in practice, the money-driven propaganda efforts to shape our shared Reality toward their own ends must be vigorously resisted.

[CaptTom]

Our knowledge is imperfect. We don't know everything. So what do we do about it?

Abandon all common sense and go with our "gut feel" or, more likely, whatever belief most closely resembles our personal preference or political bias?

Should we not even try to push the boundaries of knowledge, because there's an outside chance that, even though our research has advanced science, part of our answer may be found later to be more complex or nuanced than we originally thought?

Honestly, some people will use any justification to stick their heads in the sand!

[GordMay]

[IMG]https://cdn-images-1.medium.com/max/800/1*L2Stp62lKNwHc4j3UgVi9w.png[/IMG]

[Singularity]

Originally Posted by GordMay

“Why Most Published Research Findings Are False” ~ by John P. A. Ioannidis.....


Note: This article didn't go unchallenged. See "Related PLOS Articles", to the right of the main article.

This subject of bias and methodology (i.e. human nature) is quite old (thousands of years?) and is known to people who know how to read research in their field. Discussing the etiology of the phenomenon is problematic in mixed company as it ordinarily requires reference to religion and politics.

Why the intense interest...in a forum where religion and politics cannot frankly be discussed? To repetitively present the topic is curious in that it effectively says "hey, there's a problem with intellectuals" without being able to discuss what the real problem is. What is the intent or goal here?

https://en.wikipedia.org/wiki/Anti-intellectualism

[SailOar]

[For those who, like me, couldn't see the image Gord posted in #10]

[Dave_S]

It's simple...... truth to individuals is what they perceive to be true, it can be unrelated to actual truth. How people perceive an issue is their truth it is not tied to the actual truth at all.

Convince a majority to perceive an issue your way and the minority are suddenly fools.

[gamayun]

"Most" How freaking scientific is that?!

[StuM]

Originally Posted by gamayun

"Most" How freaking scientific is that?!

Would you prefer "more than 50%" ?