Skip to main content

Dr. Barry Marshall as an example of Type II error.

I just used this example in class, and I realized that I never shared it on my blog. I really love this example of Type II error (and some other stuff, too). So here it goes.

http://www.achievement.org/autodoc/page/mar1int-1


Type II errors. Missing something that is there. My favorite example of this is the story of Dr. Barry Marshall. I like it because it involves a hard-working scientist betting on himself and winning big and his big win has saved and improved countless lives. I also think that it is analogous to the replication crisis (which, in and of itself, seems to be highlighting instances of Type II error, eh?). Also, some correlations not equaling causation.

So, Barry Marshall. He is an Australian physician and researcher, and he studies stomachs. And he had plenty of patients with stomach ulcers, and he saw firsthand the suffering of his patients and death from ulcers and stomach cancer.

When Dr. Marshall was going through his medical training and the beginning of his medical career, the prevailing wisdom was that stress caused ulcers. And if you had ulcers, opportunistic bacteria called H. pylori would then prey upon the ulcer.

But this had never been proven. It was just widely accepted. But as your students should understand, correlation does not equal causation. At this point in the lecture, I ask my students to raise their hands if they experience stress. They all raise their hands. I then ask my students to raise their hands if they have a nose. I then try to argue that humans must have noses because of stress. Just because two things co-occur does not mean that one is causing the other.

Anyway, Dr. Marshall argued that the causal chain was entirely wrong and that H. pylori caused ulcers, not that H. pylori was attracted to pre-existing ulcers. This is significant. The initial understanding of causality would suggest that you should practice yoga to cure ulcers. Dr. Marshall's view, however, indicates that antibiotics could effectively treat ulcers. 

So he studied H. pylori. And he became increasingly convinced that the bacteria not only caused ulcers but also stomach cancer.

Dr. Marshall wanted to test his hypothesis, but animal modeling testing was challenging to conduct because H. pylori only lives in primates (rats or mice would not do). And he didn't have those and couldn't afford those. Funding, amIrite? 

Dr. Marshall couldn't get permission for human trials, either. So he decided upon a case study. He ingested a broth containing one of his patient's H. Pylori cultures. And then he got ulcers. And then he conducted further research, which was largely ignored by his peers for a long time. Still, he kept believing in himself and eventually...won a Nobel Prize for coming up with a new course of treatment that cures ulcers and has all but eliminated stomach cancer in the Western world. I know, right?

But he was almost resigned to the file drawer. He wasn't committing the Type II error, but the rest of medicine was because they weren't paying attention to his research or taking it seriously enough.

Anyway, I really, really get into telling this story. Because it is a great story. My students love it. The story is engaging in general but especially helpful as I teach many pre-PT, PA, OT, and nursing students.

Here are some articles written about Dr. Marshall, which you can read on your own or maybe use in class. They explain how Dr. Marshall uncovered this mystery by carefully observing patients who received antibiotics not for their stomach issues, but for other medical conditions. At the same time, these patients also happened to have ulcers. The articles also highlight the role of Big Pharma and the media in spreading the story, helping the antibiotic cure finally get the attention it deserved.

http://discovermagazine.com/2010/mar/07-dr-drank-broth-gave-ulcer-solved-medical-mystery

http://blogs.scientificamerican.com/guest-blog/when-scientists-experiment-on-themselves-h-pylori-and-ulcers/

https://www.nobelprize.org/nobel_prizes/medicine/laureates/2005/marshall-bio.html


https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2661189/

Comments

Popular posts from this blog

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr.  Molly Metz maintains a curated list of hilarious "How you doing?" scales.  2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables.  So, I decided to create a post about three ways to use these scales in your stats classes:  1) Teaching the basics of variables. 2) Nominal vs. ordinal scales.  3) Daily check-in with your students.  1. Teach your students the basics...

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing,  I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.

If your students get the joke, they get statistics.

Gleaned from multiple sources (FB, Pinterest, Twitter, none of these belong to me, etc.). Remember, if your students can explain why a stats funny is funny, they are demonstrating statistical knowledge. I like to ask students to explain the humor in such examples for extra credit points (see below for an example from my FA14 final exam). Using xkcd.com for bonus points/assessing if students understand that correlation =/= causation What are the numerical thresholds for probability?  How does this refer to alpha? What type of error is being described, Type I or Type II? What measure of central tendency is being described? Dilbert: http://search.dilbert.com/comic/Kill%20Anyone Sampling, CLT http://foulmouthedbaker.com/2013/10/03/graphs-belong-on-cakes/ Because control vs. sample, standard deviations, normal curves. Also,"skewed" pun. If you go to the original website , the story behind this cakes has to do w...