Posts filed under General (3152)

From the Herald

According to a new study by computer scientists at Columbia University and the French National Institute, 59 per cent of links shared on social media have never actually been clicked: In other words, most people appear to retweet news without ever reading it.

Perhaps appropriately, the Herald passed on this story from the Washington Post without passing on their link to the research.

If you were reading carefully, you might notice the last part of the paragraph doesn’t actually fit the rest: it isn’t that ‘most people‘ retweet news without ever reading it, it’s that most retweets are done without reading (or before reading).  Even with that caveat, the research says that headlines matter — and I’m going to keep complaining about them.

The main focus of the research was something different, though. They were comparing clicks on the ‘primary’ URLs from the media site itself with the clicks on shortened URLs produced by readers.  Although the primary URLs had the majority of ‘impressions’, the secondary URLs added up to more clicks.  That is, when news stories are actually read via Twitter, more often than not it’s because of a personal recommendation by someone else who has actually read the story.

• Randomized controlled trial of police foot patrols, near Cambridge.

• How the Financial Times does data visualisation

• An interview with economist Claudia Goldin on the mechanisms behind the gender pay gap

• Harkanwal Singh from the Herald, talking at the NZ Open Data showcase

• The impact of open data on cities.

• The six-year war for NZ weather data (Philip Duncan isn’t unbiased on this, but he knows what he’s talking about)

So, there’s a new IARC cancer monograph out, but this one is disappointingly un-scary. (Here’s the Q&A)

There are two basic points. First, coffee looks safe. Officially it’s “inadequate evidence”, but that basically means “if we were in the business of calling things ‘safe’, coffee would be on the list”.  There has been enormous effort over decades to find health risks of coffee for all sorts of diseases, with extremely limited success. Coffee can make it harder to fall asleep, and that’s about it.

The second point is about ‘very hot drinks’. These are listed as ‘probably carcinogenic’, meaning there’s some evidence that regular consumption increases the risk of oesophageal cancer  (not that you’ll probably get cancer if you drink them).  By ‘very hot’, they mean very hot,  over 65°C when consumed, which is relatively unusual in New Zealand.  Here, it’s alcohol and smoking that are the main risks for oesophageal cancer.

The Immigration Minister, Michael Woodhouse, was on RadioLive

Per capita, New Zealand is ranked about 90th in the world for the number of refugees it accepts. Mr Woodhouse says this low ranking isn’t the Government’s fault — its quota puts New Zealand at “about seventh or eighth”. It’s refugees turning up unannounced that puts other countries ahead — like Jordan taking in refugees from the Syrian civil war, for example.

“I don’t want to get into a game of statistics, but we can be pretty pleased with what. We can say seventh, you can say 90th.”

When you have answers that differ that much, it’s either because someone has the numbers wrong, or (as in this case) because they are answers to different questions. When you have answers to different questions, the right statistical approach isn’t to look at the answers and decide which one you like, it’s to look at the questions and ask which is the right one.  That is, should we regard refugee numbers as basically about resettlement quotas managed through UNHCR, or as including asylum seekers?

People setting off on their own into neighbouring countries is, has always been, and probably always will be the main way they become refugees. The refugee resettlement process is a way for countries who aren’t within walking/driving/sailing distance of a humanitarian disaster to contribute and to perform some of their duty to the international community.  But the refugees who turn up unannounced, not the tidily resettled ones, are the primary and usual case. They should be included in the count unless there’s some special reason occasionally not to.

New Zealand doesn’t accept many refugees — and most countries probably wouldn’t if they could avoid it. Germany and Turkey are currently handling very high numbers because of asylum seeker fleeing the Syrian crisis, but had much lower numbers ten years ago. But German and Turkey really are accepting more refugees now. If you were in Mr Woodhouse’s ‘game of statistics’ and you were handed the ‘no, nothing has changed much’ side of that argument, you would lose.

New Zealand accepts a very low number of refugees either per capita or per unit GDP.  Some people are happy with that. Many people, probably, are happy that it’s not ten or twenty times larger, as in several European countries. But it is a very low number and people who don’t want it to change should be honest about that.

In any case, whether we count qualifying asylum-seekers or just resettled refugees, whether we look per capita or per dollar of GDP, there’s one consistent finding. We accept fewer refugees than Australia.

Team Ratings for Round 15

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 107 matches played, 63 of which were correctly predicted, a success rate of 58.9%.
Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 15. 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.

• from Wired: Transitland collects and aggregates transit data feeds from around the world. Though apparently not this part of the world

• Another great New York Times interactive, on US voting patterns.

• Unusual maps: a sailing map from the Marshall Islands, via Pitt Rivers Museum, Oxford

• The Royal Statistical Society ‘Statistical Excellence in Journalism’ awards

• How do you study the impact of changes from the ‘sharing economy’?  Andrew Gelman and Tom Slee on AirBNB “Academics now tend to ask me (a) how to refer to the data set, and (b) how they can validate it for publication purposes, to which I generally reply (a) I have no idea, and (b) I have no idea”. Sarah Emerson on Uber

There’s another neat interactive map at Herald Insights, this time of meshblock-level data on assaults in public places reported to the police. It’s a good job, but I still want to talk about some of the limitations forced on the graphics by the available data.

The most obviously strange thing about the map is the hospitals: in Auckland, two of the big hotspots are Auckland City Hospital and Middlemore Hospital. When we talk about hospitals being dangerous places, we usually mean surgical errors or drug-resistant bacteria, not assault. There are two relatively boring reasons that the hospitals stand out, which they share with the town and city centres: the hospitals have a lot of people in them, and they are public places.

In the Herald map, the colour coding reflects the number of reported victimisations, not a rate per capita.  That’s because the right population of capitas is hard to define and not readily available.  We know the number of people who live in each meshblock, and the number who work in each meshblock, but the assaults are those in public places. When you’re at home — and for many people, when you’re working — you aren’t in a public place.   There isn’t easily-available data on the number of people in public places, at meshblock resolution, for the whole country.

The other question the hospital data should raise when talking about the most dangerous areas is ‘dangerous to whom’? Who gets assaulted in hospitals?  I don’t know, but I’d expect staff are at reasonably high risk, and so are people who have already been fighting before they arrived.  It might well be that hospitals are pretty safe for people just going there because their chest hurts or they decided to mow the lawn barefoot.

If you’re in New Zealand, there’s a good chance you’ve seen the Stroke Foundation’s new TV ad campaign describing how to recognise a stroke and what to do about it (get the person to hospital Right Now). I often criticise the evidence behind health stories in the news, so it’s worth looking at how different this is.

A Herald story says

Up to half of all stroke cases could be treated with clot-busting drugs if they arrived within three hours of the stroke’s onset at a hospital.

That’s a little optimistic. There are basically three categories:

• strokes caused by bleeding
• strokes caused by clots, where the brain cells haven’t had time to die
• strokes caused by clots, but where the brain cells have had time to die

In the second group, dissolving the blood clot is helpful — it reduces the risk of both death and disability. In the first group it’s definitely harmful, and in the third group it’s unhelpful and risks triggering bleeding. 

If you get a stroke victim to hospital fast, there’s a good chance of getting them through emergency-room triage and diagnosis, and into a CT scan that can distinguish between groups one and two before it’s too late. But even if you react quickly, that’s a lot of things that have to go right — and a lot of them have to happen after you get to hospital.  The current NZ stroke guidelines say that treating 20% of cases is a realistic target: a bit less than half of those who could benefit in a perfect world.

So, how do we know the treatment is helpful, and for whom?  As with clot-dissolving treatment for heart attacks, this isn’t easy.  In particular, it’s fairly obvious which patients are harmed by treatment — they end up with bleeding in their brains — but it’s much harder to tell which patients are helped, and by how much.

The only solution is randomised trials, where patients were randomly assigned to clot-dissolving drugs or the standard treatment.  These trials need careful design, both practically and ethically. You’re introducing new diagnosis and treatment steps into over-stressed hospital emergency rooms; you’re using a treatment that might be life-saving or lethal; you’re targeting people who (by definition) don’t have their brains in good working order.  The trials were done: we now have 27 trials in 10,000 patients, and clot-dissolving treatment does more good than harm — unambiguously, if started within 3 hours from the start of symptoms and probably somewhat later, but not the next day.

In terms of evidence, this isn’t at the levels of getting vaccinated and stopping smoking, but it’s miles ahead of the evidence around fish oil or vitamin supplements or coconut oil or kids these days and their phones and internets.

Team Ratings for Round 14

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 99 matches played, 58 of which were correctly predicted, a success rate of 58.6%.
Here are the predictions for last week’s games.

Predictions for Round 14

Here are the predictions for Round 14. 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.

Russell Brown interviews Ben Goldacre:

Have the media got any better or worse at science in the time you’ve been writing about these issues?

Ha! Well, I’m not aware of any longitudinal studies that would make a fair comparison over time to say if they’ve got better. But I think the incredibly refreshing thing is that they’ve become less relevant. Wen I started writing about this stuff 15 years ago, mainstream media were the only game in town. It’s incredible to think that 15 years ago, you couldn’t talk back. The internet was not like it is today.