Posts from August 2017 (43)

There’s a bunch of web pages/apps out there that supposedly help you to decide who to vote for.

On the Fence: This one asks you to move a slider to ‘balance’ competing principles, then works out which party you agree with.

There are some obvious problems. First, the scale isn’t clearly calibrated.  If you’re at 50:50 on government vs private-sector roles in providing affordable housing, does that mean you think 50% of it should be state houses, or that it should all be state-owned but built by private sector construction companies, or something vague and woolly?

Second, as lots of people have pointed out, there’s some false dichotomies there, like the privacy:security tradeoff.

Perhaps more important, when there is a genuine tradeoff, it’s a genuine tradeoff. You typically can’t decide it by abstract principle without reference to the facts.

Vote Compass:  This one takes advantage of the empirical observation that people’s voting preferences compress fairly well into two dimensions.  The questions are much more clearly calibrated: eg, the affordable-housing one is “The government should build affordable housing for Kiwis to buy” with a ‘Strongly agree” to “Strongly disagree” scale.

Most usefully, there’s a tool for you to explore how your position differs from that of the parties on each of the questions, and to reweight the results depending on which issues you care about.  Annoyingly, there’s a category “Moral Issues” that includes marijuana legalisation but not the questions about refugees or climate-change or affordable housing

Policy: The Spinoff has a tool that seems philosophically different from the others. It has much more emphasis on comparing actual party policies and less on trying to find out what your ideal party would be. As a result, it’s less useful if you want to be told what you think, but might be more useful if you want to look at specific policies. Whether you do, I suppose, depends on how much you believe the policies — especially from the minor parties, where you’d need to know how the policies rank in their actual negotiating position for coalition or confidence & supply.

Team Ratings for Round 25

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 176 matches played, 107 of which were correctly predicted, a success rate of 60.8%.
Here are the predictions for last week’s games.

Predictions for Round 25

Here are the predictions for Round 25. 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 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 7 matches played, 5 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for Round 2

Here are the predictions for Round 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.

Team Ratings for Round 7

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 18 matches played, 11 of which were correctly predicted, a success rate of 61.1%.
Here are the predictions for last week’s games.

Predictions for Round 7

Here are the predictions for Round 7. 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.

There’s a story in New Scientist, and in the NY Daily News, based on this research paper, saying that choosing alternative treatment instead of conventional treatment for cancer is bad for you.

The research is well done: they looked at the most common cancers in the US and found a small set of people who turned down all conventional treatment in favour of ‘alternative’ medicine.  They matched these people on cancer type, age, clinical group stage, what other disease they had, insurance type, race, and year of diagnosis, to a set who did get conventional treatment.   Even after all that matching, there was a big difference in survival.

There are two caveats to the story. First, this is people who turned down all conventional treatment, even surgery. That’s rare. In the database they used, 99.98% of patients received some conventional treatment. It’s much more common for people to receive some or all of the recommended conventional treatment, plus other things — not ‘alternative’ but ‘complementary’ or ‘integrative’ medicine.

Second, the numbers are being misinterpreted.  For example, New Scientist says

Among those with breast cancer, people taking alternative remedies were 5.68 times more likely to die within five years.

The actual figures were 42% and 13%, so about 3.1 times more likely. Here’s the graph

Similarly, the New Scientist story says

They found that people who took alternative medicine were two and half times more likely to die within five years of diagnosis.

The actual figures were 45% and 26%; 1.75 times more likely.

What’s happening is a confusion of rate ratios and actual risks of death; these aren’t the same.  The rate (or hazard) is measured in % per year; the risk is measured in %.  The risk is capped at 100%; the rate doesn’t have an upper limit.   Because of the cap at 100%, risk ratios are mathematically less convenient to model than rate ratios. As a tradeoff, it’s harder to explain your results using rate ratios. The Yale publicity punted on the issue, not mentioning the numbers and leaving reporters to get it wrong.  When this happens, it’s the scientists’ fault, not the reporters’.

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 25 2017.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of August 19 – 25 2017 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…)

If you’d like to comment on or debate any of this week’s Stat of the Week nominations, please do so below!

Via GeoNet, a magnitude 4.5 quake south of Dannevirke (blue box)

The squares are reports of shaking. The big cluster is Palmerston North, with secondary clusters in Feilding and Ashhurst: there are more people who felt the quake there because there are more people there.  See also XKCD

Q: Did you see avocado gives you breast cancer?

A: Me?

Q: Well, women with mutations in the BRCA genes, such as Angelina Jolie

A: 🙄

Q: “Women with the faulty ‘Angelina Jolie’ gene should cut back on trendy avocado-based breakfasts to slash their chances of cancer.”

A: No.

Q: So the study wasn’t in women?

A: No. Or avocados.

Q: Mice

A: Not even. Cells in a lab. (press release)

Q: And the avocados?

A: The cells were given extra folate.

Q: And they got cancer?

A: No, they died.

Q: Then why is there a cancer story?

A: The researchers speculated that folate could be part of a future treatment for BRCA-damaged tumours.

Q: That’s kind of not what the Herald says

A: No, but they did get the story from the Daily Mail.

Q: So what do the researchers say about avocados?

A: They don’t mention avocados

Q: Ok, what do they say about folate, then?

A: “The authors caution that no conclusions should be drawn about whether there is any overall effect in a living animal consuming folate.”

Q: So it wasn’t the press release this time

A: No, this looks like it’s down to the Daily Mail.

• “Is it legal for me to violate Terms of Service in order to collect data for a research project?” (in the US). Casey Fiesler on law and ethics of scraping

• My first boss as a statistician. John Simes, has won the University of Sydney Vice-Chancellor’s Award for Excellence. Among other things, he was one of the early proponents of universal clinical trial registration. In 1986 he wrote about the impact of publication bias on treatment choice in cancer.

• Good discussion of virtues and flaws of Sankey diagrams for visualising flows (via Mara Averick).  Also, if you’re interested in data science tools and explanations, you should follow Mara on Twitter @dataandme

• A teaching example based on a baseball/brain cancer ‘cluster’ that didn’t hold up.  Much smaller numbers than the brain injury problems in US football or even rugby, and less prior plausibility.

• Guidelines on “trusted data use” from the NZ Data Futures partnership

• The US is having a census in 2020 — the Constitution says so. It could be a mess.  Ours, next year, looks to be in better shape.

• How much copper do you get out of a copper mine: visualisation

• It’s not just New Zealanders who have order of magnitude-and-units problems. From The New Yorker, via Felix Salmon