Stats Chat

Team Ratings for Week 12

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 85 matches played, 57 of which were correctly predicted, a success rate of 67.1%.
Here are the predictions for last week’s games.

Predictions for Week 12

Here are the predictions for Week 12. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 1

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Predictions for Round 1

Here are the predictions for Round 1. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Week 3

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 10 matches played, 5 of which were correctly predicted, a success rate of 50%.
Here are the predictions for last week’s games.

Predictions for Week 3

Here are the predictions for Week 3. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

• The “cancer mornings” paper now has an Editors Note “The editors are issuing this note to alert readers that concerns have been raised regarding inconsistencies between the registration record of this trial on clinicaltrials.gov and published version the study protocol, as well as with some of the findings in this study. Editorial action will be taken as appropriate once an investigation of the concerns is complete and all parties have been given an opportunity to respond in full.”  For people more familiar with politics, on the controversial/embattled/disgraced/former spectrum an editors note is somewhere near the controversial/embattled boundary.  In this example it’s a mixture of not believing the result is possible and some changes in the trial registration over time (as I mentioned).
• Various sources are enthusiastically repeating a claim that the Tesla Cybertruck is explodier than the notorious Ford Pinto was. The Cybertruck had had 5 fire fatalities in an estimated 34,438 vehicles, versus 27 in  3,173,491 vehicles for the Pinto.  Crudely, that’s a ratio of 17.  There’s obviously a lot of uncertainty, but a standard uncertainty interval for the relative risk goes from 5.8 to 41.  There are a few more caveats: first, one of the five Cybertruck deaths was deliberate. If we don’t count that one, the uncertainty interval is now 4 to 35. Second, the denominator isn’t that reliable for the Cybertruck.  Third, we don’t have any driving information — if the cybertrucks were driven more you might expect more fires.  Fourth, this is obviously a comparison selected after the fact, so it will be inflated and less reliable than the stats indicate.   As an illustration of the unreliability of this comparison there are claims for the Pinto that are more than an order of magnitude higher. Mother Jones, which reported the Pinto investigation, didn’t caveat the 27 deaths figure at all in its Cybertruck story.
• Marc Daalder has an interesting story at newsroom about changes in the NZ crime rate. Or, to be more precise, the NZ reported crime rate. Retail crime is one of the sectors where the numbers are driven by reporting — most robberies from shops aren’t reported because there’s no real benefit to doing so.  This is familiar in other crime areas — intimate partner violence for one — and in medical statistics, where diagnoses of, say, prostate cancer or lung cancer or melanoma are driven by testing.
• The Color Game: how well can you remember colours?
• Women’s clothing sizes: scrolly/visualisation “[at age 15] This means for the first time ever, most girls in their cohort will be able to find a size in the women’s clothing section. This will also likely be the last time this ever happens in their lives.”

A new medical study (reported here and here) used MRI to look at the shoulders of a reasonable representative sample of 602 people over 40 in Finland.  Rotator cuff abnormalities of varying apparent severity were seen in 595 of the people: that’s 99% to two digits accuracy.  Of the 602 people, 18% reported shoulder pain and the other 82% claimed their shoulders were ok (apart from being over 40).

There wasn’t much difference between the people who noticed their shoulders hurting and the ones who didn’t: here’s a graph comparing asymptomatic and symptomatic shoulders,  so someone with one bad shoulder and one over-40-but-otherwise-good shoulder is in both groups. The green at the bottom is “no abnormality”, then we progress through “tendinopathy”, “partial-thickness tear”,”full-thickness tear”.

You can see the abnormalities are a bit more severe in the symptomatic group, but not enough to make a useful diagnostic test.  On top of that, the researchers showed that the difference largely goes away when you adjust for things a doctor would have measured before doing the MRI, so the MRI really isn’t providing much useful information.

We’ve seen this before. New medical-imaging tech gets used first on people who look like they need it. A lot of people with back pain were given CT scans. These showed that people with back pain had weird misshapen spines, and often led to referrals for surgery.  It was much later that people not reporting significant back pain had their backs scanned — and they, too, often had weird misshapen spines. Spines are just badly designed and implemented.

Medical imaging can be immensely valuable: simple X-rays, CT scans, MRI, PET, and so on. One of Marie Curie’s many claims to fame was designing, deploying, and driving mobile X-ray units in the Battle of the Marne.  But with each shiny new technology for subtler and more precise imaging there’s an increasing need for control data. Marie Curie could see a piece of lead in a soldier’s heart and be confident that it wasn’t normal.  The problems we’re looking for in shoulders and spines are more complicated and comparisons are important.

Team Ratings for Week 2

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 5 matches played, 1 of which were correctly predicted, a success rate of 20%.
Here are the predictions for last week’s games.

Predictions for Week 2

Here are the predictions for Week 2. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Via the pharmaceutical chemist Derek Lowe, and also various media outlets, there is a new cancer study that randomised patients with lung cancer to get their immunotherapy infusions in the morning or the afternoon/evening.  The motivation  will have been the various not-very-convincing correlational studies where patients getting morning treatment did better on average. In those studies the differences seen were large, but the studies were small enough that only large differences could have been seen.

The new study also saw a massive difference between morning and afternoon treatment, with the estimated rate of survival without disease progression being 60% lower in the morning group. That difference was 5.5 standard errors away from zero — almost physics levels of statistical surprise.

So, what  do we check?

First: dropout. Maybe the healthy patients in the afternoon or the sick patients in the morning dropped out? No, according to the research paper everyone who was randomised was included in the final analysis.

Second: did they report what they said they would report? Up to a point, yes.  The clinical trial registry says they started out with overall survival and response rate (tumour shrinkage) as their measurements of success. They changed to progression-free survival as their headline measurement after the trial had been running for a while, which is potentially dodgy.  On the other hand, they did report overall survival, and the results are almost as good as progression-free survival.  They also reported response rate, which had unimpressive favorable results, but which is a much less important measurement.  If things had gone the other way, with good response and bad survival data I would have believed the survival data.

We should now consider whether the results make sense.  This is immunology — as Ed Yong described it for the Atlantic, “where intuition goes to die”.  Looking at the experts (Derek Lowe and the people quoted in the news stories) it seems they don’t completely believe it, but they are also unwilling to entirely disbelieve it.  The drug hangs around in the body for weeks, making a time-of-day effect surprising, but who knows?  The result agrees with past correlational research, but that past research is not very convincing. The worst that the experts quoted by Stat (a medical news site) were willing to say is that only half the eligible patients were randomised, which might mean problems in generalising the results. Fortunately, this trial will be relatively easy to replicate, directly in lung cancer, or in the range of other conditions such as melanoma or head and neck cancer where this specific antibody is used, or in the wider world of immune checkpoint inhibitors.

The possibility that’s not mentioned by any of the news stories is fraud: either faking data or faking the tidiness of the randomisation and completeness of the data. Fraud happens; it’s a definite possibility.  On the other hand, this doesn’t look like an especially attractive place to try it. Other researchers are bound to redo the experiment, and look into the details, and Big Pharma hasn’t worked out how to manufacture more than one morning per day.

I expect these results to fail to replicate, but I wouldn’t bet large amounts of money on it.

Every two years (since 1988) there is at least one round of stories about condoms at the Olympics (here’s a couple of past StatsChat posts).

Many athletes would have the funds and general executive function to be able to acquire condoms for themselves, and it’s clear that a big part of the point is safe-sex advertising. It’s relatively difficult to get a positive story about condom use into the world’s prestige press, and the Olympics are an opportunity.

Usually the story is about oversupply  (450,000 in Rio!, 200,000 Olympics-branded ones in Paris!). For a couple of Olympics the story was about social distancing (Tokyo had 110,000, but they were officially just souvenirs).

This year the story is undersupply: Milano/Cortina apparently had a mere 10,000 condoms, which ran out on day 3.  It’s possible that this is a planning failure, like the nearly-finished cable car, but it might also be that the whole advertising mission of the Olympic condoms is losing its urgency.

• The US FDA will not even review the application for Moderna’s new flu vaccine. The FDA is very careful to give itself the flexibility to do this: if they say supportive things about your trial design today there is no legal guarantee that they can’t change their minds six times before breakfast. However, they are usually reluctant to make radical changes in their advice and, for example, typically don’t require placebo controls when an existing treatment works and is already widely recommended.
• Hayden Donnell at the Spinoff did a deeply felt post on the scale of the Moa Point sewage discharges, with comparisons to everyday life. I want to quote one: “ If you started now, it would take you 2,535 years, 15 days, 13 hours, and 20 minutes of non-stop shitting to produce as much waste as the Moa Point plant is expelling onto schools of unsuspecting fish every day. From this we can deduce with a little additional calculation that the roughly 200,000 people living in Wellington City would take about four and half days to produce one day of the Moa Point poop.  Even allowing for politicians, that’s a lot of effort. The problem, of course, is dilution: a toilet flush is about 10 litres rather than the 0.1 litres the Spinoff is allowing for, and there may well be further dilution downstream.
• A set of six posts about colour (or perhaps ‘color’) from NASA
• The American Statistical Association is taking nominations for its “Excellence in Statistical Reporting” award, due March 1st.
• “And it turned out that the previous gender discrimination policy had been nothing like discriminatory enough; women were much safer drivers, and hadn’t previously been getting anything like enough credit for it.” Dan Davies’s excellent “Back of Mind” newsletter.

Team Ratings for Week 1

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Predictions for Week 1

Here are the predictions for Week 1. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.