Stats Chat

The Guardian reports “Gen Z males twice as likely as baby boomers to believe wives should obey husbands”, with similar phrasing in headlines from the Daily Mail, and the NY Post, and in the lede from the BBC. This has, unsurprisingly, caused a bit of concern.

Looking at the original information from King’s College London (research for International Women’s Day†) the trend seems to go over all ages

This seems strange. I would not have thought women’s equality had been getting steadily worse for the past eighty years. Do we just have a bad question, or a bad sample, or what? The page at King’s College shows broadly similar patterns for other gender attitude questions, though often less extreme. It’s not just the question but it might be partly the question.  In particular, there might be a carryover from ‘obey’ in wedding vows, which is not quite the same. However, “A husband should have the final word on important decisions made in his home” gets very similar answers to the “obey” question.

Here’s the worldwide comparison for the ‘obey’ question:

There’s a huge amount of variation between countries, so the results will be sensitive to how countries are combined.  Honest and competent researchers will give you this sort of information, and there is a full PDF report actually linked from the King’s College page, near the top!  It has a Technical Note on the last page that says in part

The data is weighted so that the composition of each country’s sample best reflects the demographic profile of the adult population according to the most recent census data. “The Global Country Average” reflects the average result for all the countries and markets in which the survey was conducted. It has not been adjusted to the population size of each country or market and is not intended to suggest a total result. [emphasis added]

It would be interesting to see separate trends for countries and regions, rather than suggesting a total result, when the responses from different countries are so different.

† Yes, there is. November 19.

Newsroom has a long piece on traffic congestion in Auckland in March. Near the beginning, Douglas Wilson, from the Transport Research Centre at the Uni of Auckland says

“So suddenly people say, ‘Wow, it’s taking me double the travel time to get to work. Why is that the case?’ It’s not that you’ve doubled the traffic volume. Actually, the volume has only gone up a little, proportionally, but the traffic flow has reached capacity.”

This is one of the Two Simple Facts from queueing theory, the branch of applied probability that deals with congestion in networks. These networks can be physical road networks or electronic data networks or something like a system of medical waiting lists, or something as simple as a literal queue, and what they all have in common is waiting for other users.

Queueing theory can lead to very complicated simulations and theoretical approximations, but parts of it are simple. My Two Simple Facts are

1. When you have multiple servers you should still try to have a single queue
2. A queueing system has a “capacity” and when it gets near that capacity small changes make things much worse

Most of the time, Auckland’s traffic system works reasonably well. There’s enough wiggle room for traffic to catch up around the inevitable slowdows.  When you get a big crash on the motorway or heavy rain or extra drivers, though, the whole system suddenly gets much slower. In the other direction, removing drivers after Christmas opens up the city out of all proportion to the number who leave.

Sudden slowdowns near full capacity are a pretty general property of queueing systems. We can look at them in a nice simple example — this sort of mathematical model is very useful both for understanding the general vibes and for developing theoretical tools.

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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.

Team Ratings for Round 18

Not sure how I missed posting this one, but here it is for completeness.

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 119 matches played, 94 of which were correctly predicted, a success rate of 79%.
Here are the predictions for last week’s games.

Predictions for Round 18

Here are the predictions for Round 18. 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 Delayed Games

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 93 matches played, 61 of which were correctly predicted, a success rate of 65.6%.
Here are the predictions for last week’s games.

Predictions for Delayed Games

Here are the predictions for Delayed Games. 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 19

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 126 matches played, 99 of which were correctly predicted, a success rate of 78.6%.
Here are the predictions for last week’s games.

Predictions for Round 19

Here are the predictions for Round 19. 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 4

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 15 matches played, 7 of which were correctly predicted, a success rate of 46.7%.
Here are the predictions for last week’s games.

Predictions for Week 4

Here are the predictions for Week 4. 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.

It’s impressive that someone has done a poll in the US with only 1/3 of respondents wanting to abolish ICE. It was Third Way, who would like you to think of them as moderate.

When you look more closely you can see how it was done. The 34% figure is for “We need to abolish ICE and halt all immigration enforcement inside the country”.  These two policy changes are not especially closely linked — the US had immigration enforcement for a long time before creating ICE — and the first proposal, rather than the more extreme second one, is given the headline.

In August, the Guardian and the BBC reported a successful clinical trial of an “AI stethoscope”. I’ll note at the start that this isn’t ChatGPT, it’s the older deep neural network style of AI that works more predictably and consistently.

The BBC said

These reports were based on a presentation at a scientific conference, the European Society of Cardiology meeting. Yes, the trial was called TRICORDER.  “A good name is better than precious ointment”, as the Bible tells us.

There’s some reason to think the claims are plausible.  The most important of the abnormal heart rhythms is very obvious just by taking a pulse, and doctors listen for particular heart sounds as evidence of heart failure.  So, it could be true.  The “AI stethoscope” would still have to be better than a stethoscope together with natural intelligence, but that’s why you do the trial.  The trial randomly allocated half of the GP practices to use an AI stethoscope and the other half to business as usual.

Now we have the full research paper published in Lancet.  The abstract says

Intention-to-treat analysis found heart failure detection did not differ between groups (IRR 0·94 [95% CI 0·86–1·02]); with no difference in community-based or hospital-based diagnoses (p>0·05).

That is, there isn’t good evidence of a benefit from your doctor having an “AI stethoscope” and at least for heart failure detection there’s evidence against a meaningful benefit: the uncertainty interval tops out at a 2% increase.

It’s worth emphasising that the trial had already finished last August. All that differs is the analysis.   The analysis in the conference presentation was the “per protocol” comparison: comparing people who got an AI stethoscope examination with a curated set of controls who got at least one face-to-face consultation (but not necessarily a non-AI stethoscope). In fact, they couldn’t get enough information for data linkage on all the people who got an AI stethoscope examination, so the analysis only used half of them. The published paper also reports this analysis

Use declined over time, with clinicians citing workflow barriers to sustained use. In per-protocol analyses, adjusting for patient exposure to the AI-stethoscope, detection of heart failure (IRR 2·33 [95% CI 1·28–4·26]), atrial fibrillation (IRR 3·45 [2·24–5·32]), and VHD (IRR 1·92 [1·09–3·40]) was significantly increased in the intervention group.

So, doctors didn’t use the “AI stethoscope” much, but if you compare half of the people who did get AI stethoscoped with the same number of apparently similar people in the control group of the trial, you find big differences.  This difference could be a real benefit of the new device, but we no longer really have randomised evidence on that question; we’re relying on how similar the researchers could make the treatment and control groups.

It’s still worth publishing the data, and the researchers and Lancet get credit for putting the randomised-trial analysis first in the research paper. Lancet doesn’t really get much credit for posting the results as “AI-enabled stethoscopes show promise for improving diagnosis of cardiovascular conditions, UK trial finds”.

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.