Stats Chat

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 August 22 2014.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of August 16 – 22 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.

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Predictive risk scores for re-offending are increasingly used in the US. An opinion piece in the New York Times argues this is bad

The basic problem is that the risk scores are not based on the defendant’s crime. They are primarily or wholly based on prior characteristics: criminal history (a legitimate criterion), but also factors unrelated to conduct. Specifics vary across states, but common factors include unemployment, marital status, age, education, finances, neighborhood, and family background, including family members’ criminal history.

• Jawbone (who make gadgets that tell you if you’re awake and walking around) have made some interesting graphics on sleep and activity in cities around the world.

• VentureBeat argues that doctors don’t actually care about your Jawbone and Fitbit data

• Alberto Cairo writes about media graphics and constructive criticism. He’s probably right.

• the Slate Money podcast has some nice discussion of data science jobs, from a range of viewpoints (starting at about 24:45 — or listen to the whole thing and learn about Buzzfeed and about the payday loan industry)

From the Sunday Star-Times, on fish oil

Grey and colleague Dr Mark Bolland studied 18 randomised controlled trials and six meta-analyses of trials on fish oil published between 2005 and 2013. Only two studies showed any benefit but most media coverage of the studies was very positive for the industry.

On the other hand, the CEO of a fish-oil-supplement company disagrees

Keeley said more than 25,000-peer reviewed scientific papers supported the benefits of omega-3. “With that extensive amount of robust study to be then challenged by a couple of meta-analyses where negative reports are correlated together dumbfounds me.”

In fact, it happens all the time that large numbers of research papers and small experiments find something is associated with health then small numbers of large randomised trials show it doesn’t really help.  If it didn’t happen, medical and public health research would be much faster, cheaper, and more effective. I’m a coauthor on at least a couple of those 25000 peer-reviewed papers, and I’ve worked with people who wrote a bunch more of them, and I’m not dumbfounded. You don’t judge weight of evidence by literally weighing the papers.

Mr Keeley takes fish oil himself, and believes he will “live to 70, or 80 or 90 and not suffer from Alzheimer’s.”  That’s actually about what you’d expect without fish oil. He’s 60 now, so his statistical life expectancy is another 23 years, and by 83, less than 10% of people have developed dementia.

I wouldn’t say there was compelling evidence that fish-oil capsules are useless, but the weight of evidence is not in favour of them doing much good.

There are lots of Lotto strategies based on trying to find patterns in numbers.

Lotto New Zealand televises its draws, and you can find some of them on YouTube.

If you have a strategy for numerological patterns in the Lotto draws, it might be a good idea to watch a few Lotto draws and ask yourself how the machine knows to follow your pattern.

If you’re just doing it for entertainment, go in good health.

I’ve mentioned a number of times that statistics on cancer survival are often unreliable for the conclusion people want to draw, and that you need to look at cancer mortality.  Today’s story in Stuff is about Otago research that does it right:

The report found for 11-year timeframe, cancer-specific death rates decreased in both countries and cancer mortality fell in both countries. But there was no change in the difference between the death rates New Zealand and Australia, which remained remained 10 per cent higher in New Zealand.

That is, they didn’t look at survival after diagnosis, they looked at the rate of deaths. They also looked at the rate of cancer diagnoses

“The higher mortality from all cancers combined cannot be attributed to higher incidence rates, and this suggests that overall patient survival is lower in New Zealand,” Skegg said.

That’s not quite as solid a conclusion — it’s conceivable that New Zealand really has higher incidence, but Australia compensates by over-diagnosing tumours that wouldn’t ever cause a problem — but it would be a stretch to have that happen over all types of cancer combined, as they observed.

Stuff has a story from the LA Times about exercise and breast cancer risk.  There’s a new research paper based on a large French population study, where women who ended up having a breast cancer diagnosis were less likely to have exercised regularly for the past five year period.  This is just observational correlation, and although it’s a big study, with 2000 breast cancer cases in over 50000 women, the evidence is not all that strong (the uncertainty range around the 10% risk reduction given in the paper goes from an 18% reduction down to a 1% reduction).  Given that,  I’m a bit unhappy with the strength of the language in the story:

For women past childbearing age, a new study finds that a modest amount of exercise — four hours a week of walking or more intensive physical activity such as cycling for just two hours a week — drives down breast cancer risk by roughly 10 per cent.

There’s a more dramatically wrong numerical issue towards the end of the story, though:

The medications tamoxifen and raloxifene can also drive down the risk of breast cancer in those at higher than average risk. They come with side effects such as an increased risk of deep-vein thrombosis or pulmonary embolism, and their powers of risk reduction are actually pretty modest: If 1000 women took either tamoxifen or raloxifene for five years, eight breast cancers would be prevented.

By comparison, regular physical activity is powerful.

Using relative risk reduction for the (potential) benefits of exercise and absolute risk reduction for the benefits of the drugs is misleading. Using the breast cancer risk assessment tool from the National Cancer Institute, the five-year breast cancer risk for a typical 60 year old is perhaps 2%. That agrees with the study’s 2000 cases in 52000 women followed for at least nine years.  If 1000 women with that level of risk took up regular exercise for five years, and if the benefits were real,  two breast cancers would be prevented.

Exercise is much less powerful than the drugs, but it’s cheap, doesn’t require a doctor’s prescription, and the side-effects on other diseases are beneficial, not harmful.

A nice story in the Herald about a randomised trial of hand sanitiser dispensers in schools.

The study, published today in the journal PLoS Medicine, found absence rates at schools that installed dispensers in classrooms as part of the survey were similar at those “control” schools which did not.

There’s even a good description of the right way to do sample size calculations for a clinical trial

Beforehand, the authors believed a 20 per cent reduction in absences due to illness would be important enough to merit schools considering making hand sanitiser available, so designed the study to detect such a difference.

“Some previous studies suggested that there could be a bigger effect than that, but we wanted to be sure of detecting an effect of that size if it was there,” Dr Priest told the Herald.

That is, the study not only failed to find a benefit, it ruled out any worthwhile benefit. Either Kiwi kids are already washing their hands enough, or they didn’t use the supplied sanitiser.

My only quibble is that the story didn’t link to the open-access research paper.

Team Ratings for Round 23

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 160 matches played, 91 of which were correctly predicted, a success rate of 56.9%.

Here are the predictions for last week’s games.

Predictions for Round 23

Here are the predictions for Round 23. 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

Here are the team ratings prior to Round 1, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

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.