Stats Chat

I don’t want to get into the general business of election fact-checking, but we have a Stat-of-the-Week  nomination for a statement that is (a) about a specifically statistical issue at the high-school level, and (b) unambiguously wrong.  From Richard Prebble’s “The Letter”:

 Cunliffe is basing Labour’s election campaign around the claim that inequality is growing. Fact check: inequality is falling and New Zealand remains a very equal country. The claim that around a quarter of a million children are in poverty is dubious, to say the very least. Cunliffe says households in poverty have less than 60 percent of the medium income after housing costs. If Bill Gates came to live in New Zealand, the medium income of the country would rise and, according to that logic, more children would be in poverty.

David Cunliffe, as you presumably know, talked about the median, not “medium”; the use of a fraction of median income as a relative poverty threshold is very common internationally. The reason for using the median is precisely that the median income of the country would not rise if a few billionaires were added to the population. The median, the income of the household in the middle of the income distribution, is very insensitive to changes in or additions of a few values. That’s what it’s for.

While I’m writing, I might as well mention the inequality statistics.  Mr Cunliffe isn’t making up his figures on children in poverty; they can be found in the 2014 Household Incomes Report from the Ministry of Social Development [update: that figure is 260000, which matches what The Letter reported was said, but the actual speech said 285000]. The report also gives trends in the Gini index of inequality and in the proportion of income spent on housing.  StatsNZ gives trends in the ratio of 80th to 20th percentile of income, before and after housing costs. The details of trends in inequality depend on how you measure it, but by these measures it is neither falling, nor notably low internationally.

The story about cycling and prostate cancer in the Herald (or the Daily Mail) is a good opportunity to look at some of the rules of thumb for deciding which stories to read or believe:

Firstly, would you have heard if the results were the other way around? Almost certainly not: prostate cancer wasn’t the main point of this study, and there wasn’t a previously-suspected relationship.

Second, for cancer specifically, is this mortality or diagnosis data? That is, are we seeing an increase in detection or in cancer? This is diagnosis data; so it could be just an increase in detection. The researchers were confident it wasn’t, but we must remember the immortal words of Mandy Rice-Davies

Thirdly, what sort of study is it? Obviously it can’t be experimental, but a good study design would be to ask people about cycling (or even better, measure cycling) and then see whether it’s the bike fanatics who develop cancer. This study was a self-selected survey of cyclists, getting self-reported data about past cycling and past diagnosis of prostate cancer. It’s a fairly extreme sample, too: half of them cycle more than 5.75 hours per week.

Fourth, how strong is the evidence of association, and what sort of sample size are we looking at? The association is just barely statistically significant (p=0.046 in one model, p=0.025 in a second), and there are only 36 prostate cancer cases in the sample.  It’s pretty borderline.  The estimated relative risk is huge, because it has to be given the sample size, but the uncertainty range is also huge. The confidence interval on the relative risk of 5 reported by the Herald goes from 1.5 to 18.

Fifth, what does previous research say? This is in the story

‘To the best of our knowledge, this is the first study to demonstrate an association between prostate cancer and cycling, so there are no studies hypothesizing a pathophysiological mechanism for such a link.’

Sixth, what do other experts think? We don’t know. The closest thing to an independent comment is this in the press release

“Physicians should discuss the potential risks and health benefits of cycling with their patients, and how it may impact their overall health,” says Ajay Nehra, MD, Editor-in-Chief of Journal of Men’s Health and Chair, Department of Urology, Director, Men’s Health, Rush University Medical Center, Chicago, IL.

He could have said that without reading the paper.

In summary, there’s borderline evidence from a weak study design for a sensational finding that isn’t supported by any prior evidence. This is fine as research, but it shouldn’t be in the headlines.

You can read the research paper here for the next month, and the journal press release here.

In March, I wrote

The Herald has a story about a potential blood test for dementia, which gives the opportunity to talk about an important statistical issue. The research seems to be good, and the results are plausible, though they need to be confirmed in a separate, larger sample before they can really be believed. …

 But it’s the description of the accuracy of the test that might be misleading.

There’s a Herald story today about new test; the same comments apply, except that the research paper is open-access

Team Ratings for Round 18

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 122 matches played, 68 of which were correctly predicted, a success rate of 55.7%.

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 Round 19

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 113 matches played, 73 of which were correctly predicted, a success rate of 64.6%.

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.

Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.

Here’s how it works:

• Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday July 11 2014.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of July 5 – 11 2014 inclusive.
• Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.

Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.

(more…)

Back in 2010, a piece in Slate pointed out that a country’s success in the 2010 and 2006 World Cup knock-out rounds was strongly correlated with the proportion of the population infected by Toxoplasma gondii.  In 2010, Toxoplasma seroprevalence predicted all eight knockout-round wins; in 2006 it predicted seven of eight.

Toxoplasma, in case you weren’t introduced when you met it, is a single-celled organism that can live, and reproduce asexually, in pretty much any warm-blooded animal, but can only reproduce sexually in the guts of cats. That’s not the interesting part. The interesting part is that in rodents the parasite has effects on the brain, making the animal less cautious and more likely to end up in the gut of a cat. There’s some evidence Toxoplasma also has effects on human behaviour, though that’s still controversial.

Now, in 2014, I see a Tweet from Australian biologist Michael Whitehead

@mmcgowan569 @amandahoh @NickEvershed Toxoplasmosis gondii seroprevalence predicts 100% in knockouts by my data. (Not kidding).

— Michael Whitehead (@Mikey_Whitehead) July 4, 2014

So, three times is enemy action?

There are good reasons to be sceptical: the football rankings haven’t changed all that much since 2006, so this isn’t really three independent tests. Also, the seroprevalence data is for the countries as a whole, not for the team members.  Still, in contrast to the predictions using Octopus vulgaris in the last World Cup, it’s not completely out of the question that there could be a real effect.

• “There are advantages and disadvantages for reporting the median, but over time it has become common practice worldwide to report market benchmark prices as the median.” from a good explanation at interest.co.nz

• The maximum, on the other hand, is rarely a good summary on its own. This Herald story on slow licence suspensions is not an exception. A median or 90th percentile, or proportion taking longer than a reasonable duration would have been good additions. Also, how many licence suspensions are there for accumulated demerits?

• TheWireless is having a ‘theme’ on Risk. It’s pretty much non-quantitative, which I think misses something, but they aren’t trying to draw unwarranted generalisations from qualitative data. I liked the story on yellow-stickered earthquake-risk buildings; an interesting counterpoint is Eric Crampton’s post on house-hunting in Wellington.

• “Measure twice; cut once” is the old saying. It’s good that the government’s welfare reform program is being evaluated. Not so good that the evaluation plan is secret even under OIA.

• Interestingly, the retracted and recently republished paper on GMOs and Roundup  (previous StatsChat coverage)wasn’t peer-reviewed. Or, rather, it wasn’t peer-reviewed again — the journal decided that the initial review before the retraction was enough. This was not made very clear in the paper or press material.

From the Herald

A new scientific test is able to detect which 14-year-olds will become binge drinkers by the time they hit 16.

A study published in the journal Nature describes how scientists have developed a system that weighs up a range of risk factors and predicts – with about 70 per cent accuracy – which teens will become heavy drinkers.

That’s true, but the definition of accuracy is doing quite a bit of work here.

We don’t have figures for 16 year olds, but according to the Ministry of Health about 20% of 15-17 year olds have ‘hazardous drinking patterns.’ That means I can predict with 80% accuracy without even needing to weigh up a range of risk factors — I just need to predict “No” each time. Parents, teachers, or people working with youth could probably do better than my 80% accuracy.

The researchers found that their test correctly classified 73% of the non-binge-drinker and 67% of the binge drinkers, which means it would get 72% of people classified correctly. That’s rather worse than my trivial “the kids are ok” predictor. In order to be any use, the new test, which combines brain imaging and detailed interviews, needs to be set to a higher threshold, so it predicts fewer drinkers.  The researchers could have done this, but they didn’t.

Also, in order to be any use, the test needs to identify a group who will selectively benefit from some feasible intervention, and there needs to be funding to supply both this intervention, and the cost of doing long interviews and fMRI brain imaging on large groups of teenagers. And that needs to be the best way to spend the money.

Team Ratings for Round 17

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 117 matches played, 67 of which were correctly predicted, a success rate of 57.3%.

Here are the predictions for last week’s games.

Predictions for Round 17

Here are the predictions for Round 17. 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.