Be Careful Of P-Hacking

Vincent Granville discusses the problem of p-hacking:

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 the 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 who have lost faith in science.

The trick consists of repeating an experiment sufficiently 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

Wansink is a charlatan.  But beyond p-hacking is Andrew Gelman and Eric Loken’s Garden of Forking Paths.  Gelman’s blog, incidentally (example), is where I originally learned about Wansink’s shady behaviors.  Gelman also warns us not to focus on the procedural, but instead on a deeper problem.

Related Posts

P-Hacking and Multiple Comparison Bias

Patrick David has a great article on hypothesis testing, p-hacking, and multiple comparison bias: The most important part of hypothesis testing is being clear what question we are trying to answer. In our case we are asking:“Could the most extreme value happen by chance?”The most extreme value we define as the greatest absolute AMVR deviation from […]

Read More

Feature And Text Classification Using Naive Bayes In R

I wrap up my series on the Naive Bayes class of algorithms, finally writing some code along the way: Now we’re going to look at movie reviews and predict whether a movie review is a positive or a negative review based on its words. If you want to play along at home, grab the data set, […]

Read More

1 Comment

Comments are closed

Categories

September 2018
MTWTFSS
« Aug Oct »
 12
3456789
10111213141516
17181920212223
24252627282930