/* ---- Google Analytics Code Below */

Saturday, October 06, 2018

Manipulating P Values

More from Vincent Granville in DSC on P-Values and their misuse.  I recall the repeating experiments as a trick in an early statistical analysis course.  perhaps this is more common in other areas, but never saw this kind of misuse in engineering.  Useful read here.

Statistical Significance and p-Values Take Another Blow

I read an article this morning, about a top Cornell food researcher having 13 studies retracted, see here. It prompted me to write this blog. It is about data science charlatans and unethical researchers in Academia, destroying the value of p-values again, using a well known trick called p-hacking, to get published in top journals and get grant money or tenure. The issue is widespread, not just in academic circles, and make people question the validity of scientific methods. It fuels the fake "theories" of those have lost faith in science.

The trick consists of repeating an experiment sufficient many times, until the conclusions fit with your agenda. Or by being cherry-picking about the data you use, or even discarding observations deemed to have a negative impact on conclusions. Sometimes, causation and correlations are mixed up on purpose, or misleading charts are displayed. Sometimes, the author lacks statistical acumen.

Usually, these experiments are not reproducible. Even top journals sometimes accept these articles, due to:

Poor peer-review process

Incentives to publish sensational material

By contrast, research that is truly aimed at finding the truth, sometimes does not use p-values nor classical tests of hypotheses. For instance, my recent article comparing whether two types of distributions are identical, does not rely on these techniques. Also the theoretical answer is know, so I would be lying to myself by showing results that fit with my gut feelings or intuition. In some of my tests, I clearly state that my sample size is too small to make a conclusion. And the presentation style is simple so that non-experts can understand it. Finally, I share my data and all the computations. You can read that article here. I hope it will inspire those interested in doing sound analyses. ... "

No comments: