April 4, 2017

Attack of the killer margarine: the reboot

In 2015, the Herald had a story from the Daily Telegraph on the alleged risks of margarine:

Saturated fat found in butter, meat or cream is unlikely to kill you, but margarine just might, new research suggests.

Traditionally people have been advised to reduce animal fats, but the biggest ever study has shown they do not increase the risk of stroke, heart disease or diabetes. However, trans fats, found in processed foods such as margarine, raise the risk of death by 34 per cent in less than a decade.

“For years everyone has been advised to cut out fats,” said study lead author Doctor Russell de Souza, an assistant professor in the Department of Clinical Epidemiology and Biostatistics, at McMaster University in Canada.

It’s a bit unclear exactly what “raise the risk of death by 34 per cent in less than a decade” is supposed to mean, but we’ll get to that. The research paper was in the BMJ, and came out on the same day the story did.

Today, in 2017, the Herald had a story from the Daily Telegraph on the alleged risks of margarine:

Saturated fat found in butter, meat or cream is unlikely to kill you, but margarine just might, new research suggests.

Although traditionally dieticians have advised people to cut down on animal fats, the biggest ever study has shown that it does not increase the risk of stroke, heart disease or diabetes.

However trans-fats, found in processed foods like margarine raises the risk of death by 34 per cent.

“For years everyone has been advised to cut out fats,” said study lead author Doctor Russell de Souza, an assistant professor in the Department of Clinical Epidemiology and Biostatistics, at McMaster University in Canada.

It’s a bit unclear exactly what “raise the risk of death by 34 per cent in less than a decade” is supposed to mean, but we’ll get to that. The research paper was in the BMJ, and came out nearly two years before the story did.

Yes, it really seems to be the same ‘new reasearch’: Dr de Souza hasn’t just published another meta-analysis. It even seems to be the same Telegraph story; I couldn’t find a new one.

So, how scared should we be of trans fats in our diets?  Food Standards Australia New Zealand say

Monitoring of TFAs in the Australian and New Zealand food supply has found that Australians obtain on average 0.5 per cent of their daily energy intake from TFAs and New Zealanders on average 0.6 per cent. This is well below the WHO recommendation of no more than 1 per cent.

They also say that the majority of that 0.6% is made by bacteria in the rumens of cows and sheep, not by industrial hydrogenation; the evidence of harm is weaker for these natural trans fats.

Now, back to the 34% statistic. This is based on two studies. One compared the 20% of people with the highest and lowest trans fat intakes and found a rate ratio of 1.24. The other, smaller, one estimated the ratio as 1.71 between the highest and lowest 25%.   These are rate ratios estimated from people in their 60. Since the actual probability of death in any given year would have been about 1% the absolute risk increase is smaller than “34% in less than a decade” sounds — but not at all trivial.  For comparison, the all-cause mortality rate ratio for current smoking is about 3.0, or 200% higher than non-smokers.

More importantly, though, we’re talking about a lot of trans fat in these studies. In the larger study with the less-scary rate ratio, people in the lowest 20% of trans fat intake got an average of 1.6% of their calories from it. That is, the lowest-risk group were eating three times as much trans fat as an average Kiwi today.  In the smaller study, they don’t give actual trans fat information for the groups they are comparing, but the average for the whole study was about 9% of fat in the blood was trans fat: if that even roughly translates to proportions of dietary fat they were also getting more than the typical Kiwi today.

There just isn’t that much trans fat in most margarine any more, less than 1% on average (according to Food Standards Oz/NZ, table 2) . There used to be a lot, but then we found out it’s bad for you.  Those scary numbers are actually good news if they’re true: they’d measure how much better off margarine consumers are today than twenty years ago.

(via Mark Hanna)

How big is that (2)

In yesterday’s Official StatsChat Bogus Poll, about two-thirds of the respondents got one of the reasonable answers.

Here’s how we could work out most of the answer without looking it up.

First, a hectare is 10,000 square meters, or 2.5 acres (you might need to look that up).

Now, a ‘full section’ for a house is typically less than 1000 square meters (a quarter acre), so you get 10-20 of them per hectare, and maybe 100,000 of them in 7000 ha.  That’s definitely bigger than Eden Park, and it’s pretty clearly bigger than One Tree Hill Domain + Cornwall Park.  In the other direction, 100,000 full sections must be smaller than the Auckland isthmus, and so (look at a map) smaller than Manukau Harbour.

The comparison to Epsom electorate is a little harder, and you might need actual data to decide.

Now, actual data:

The areas are

Eden Park:  originally `about 15 acres’, or 6 ha

One Tree Hill Domain + Cornwall Park: 270 ha

Epsom: 20 sq km, so 2,000 ha

Manukau Harbour: 394 sq km, or 39,400 ha.

Waikato Region: 2.5 million ha.

If you look up the area of  the Auckland isthmus for comparison with Manukau Harbour, you’ll probably get a figure of 638 sq km. That’s the area of the old Auckland City: it includes the Gulf Islands that were part of the city (in particular, Great Barrier and Waiheke make up more than half of it). It’s surprisingly hard to find the area of the isthmus itself on the internet.

Super 18 Predictions for Round 7

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.

Current Rating Rating at Season Start Difference
Hurricanes 17.51 13.22 4.30
Chiefs 10.80 9.75 1.00
Crusaders 9.42 8.75 0.70
Highlanders 8.55 9.17 -0.60
Lions 7.10 7.64 -0.50
Stormers 4.09 1.51 2.60
Brumbies 3.71 3.83 -0.10
Blues 1.70 -1.07 2.80
Sharks 1.16 0.42 0.70
Waratahs 0.59 5.81 -5.20
Jaguares -1.58 -4.36 2.80
Bulls -2.38 0.29 -2.70
Force -8.24 -9.45 1.20
Reds -9.59 -10.28 0.70
Cheetahs -10.03 -7.36 -2.70
Rebels -12.72 -8.17 -4.60
Kings -17.75 -19.02 1.30
Sunwolves -19.45 -17.76 -1.70

 

Performance So Far

So far there have been 49 matches played, 39 of which were correctly predicted, a success rate of 79.6%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Highlanders vs. Rebels Mar 31 51 – 12 23.40 TRUE
2 Blues vs. Force Apr 01 24 – 15 14.60 TRUE
3 Chiefs vs. Bulls Apr 01 28 – 12 17.30 TRUE
4 Reds vs. Hurricanes Apr 01 15 – 34 -23.70 TRUE
5 Stormers vs. Cheetahs Apr 01 53 – 10 14.20 TRUE
6 Lions vs. Sharks Apr 01 34 – 29 10.10 TRUE
7 Waratahs vs. Crusaders Apr 02 22 – 41 -2.90 TRUE

 

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.

Game Date Winner Prediction
1 Hurricanes vs. Waratahs Apr 07 Hurricanes 20.90
2 Sunwolves vs. Bulls Apr 08 Bulls -13.10
3 Highlanders vs. Blues Apr 08 Highlanders 10.40
4 Brumbies vs. Reds Apr 08 Brumbies 16.80
5 Sharks vs. Jaguares Apr 08 Sharks 6.70
6 Stormers vs. Chiefs Apr 08 Chiefs -2.70
7 Force vs. Kings Apr 09 Force 13.50

 

NRL Predictions for Round 6

Team Ratings for Round 6

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.

Current Rating Rating at Season Start Difference
Storm 9.40 8.49 0.90
Raiders 8.76 9.94 -1.20
Cowboys 5.01 6.90 -1.90
Broncos 4.95 4.36 0.60
Sharks 4.70 5.84 -1.10
Panthers 4.61 6.08 -1.50
Roosters 1.19 -1.17 2.40
Sea Eagles 0.87 -2.98 3.80
Eels -0.66 -0.81 0.10
Dragons -1.85 -7.74 5.90
Bulldogs -2.91 -1.34 -1.60
Rabbitohs -3.38 -1.82 -1.60
Titans -3.48 -0.98 -2.50
Warriors -7.44 -6.02 -1.40
Wests Tigers -8.02 -3.89 -4.10
Knights -13.81 -16.94 3.10

 

Performance So Far

So far there have been 40 matches played, 22 of which were correctly predicted, a success rate of 55%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Bulldogs vs. Broncos Mar 30 10 – 7 -5.80 FALSE
2 Roosters vs. Sea Eagles Mar 31 12 – 18 5.70 FALSE
3 Cowboys vs. Rabbitohs Mar 31 20 – 6 11.40 TRUE
4 Sharks vs. Knights Apr 01 19 – 18 25.80 TRUE
5 Raiders vs. Eels Apr 01 30 – 18 13.10 TRUE
6 Storm vs. Panthers Apr 01 28 – 6 5.70 TRUE
7 Warriors vs. Titans Apr 02 28 – 22 -1.10 FALSE
8 Wests Tigers vs. Dragons Apr 02 6 – 28 0.80 FALSE

 

Predictions for Round 6

Here are the predictions for Round 6. 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.

Game Date Winner Prediction
1 Broncos vs. Roosters Apr 06 Broncos 7.30
2 Knights vs. Bulldogs Apr 07 Bulldogs -7.40
3 Panthers vs. Rabbitohs Apr 07 Panthers 11.50
4 Sea Eagles vs. Dragons Apr 08 Sea Eagles 6.20
5 Titans vs. Raiders Apr 08 Raiders -8.70
6 Cowboys vs. Wests Tigers Apr 08 Cowboys 16.50
7 Warriors vs. Eels Apr 09 Eels -2.80
8 Storm vs. Sharks Apr 09 Storm 8.20

 

April 3, 2017

How big is that?

From Stuff and the Science Media Centre

Dr Sean Weaver’s start-up business has saved over 7000 hectares of native rainforest in Southland and the Pacific

So, how much is that? I wasn’t sure, either.  Here’s an official StatsChat Bogus Poll to see how good your spatial numeracy is;

The recently ex-kids are ok

The New York Times had a story last week with the headline “Do Millennial Men Want Stay-at-Home Wives?”, and this depressing graphnyt

But, the graph doesn’t have any uncertainty indications, and while the General Social Survey is well-designed, that’s a pretty small age group (and also, an idiosyncratic definition of ‘millennial’)

So, I looked up the data and drew a graph with confidence intervals (full code here)

foo

See the last point? The 2016 data have recently been released. Adding a year of data and uncertainty indications makes it clear there’s less support for the conclusion that it looked.

Other people did similar things: Emily Beam has a long post  including some context

The Pepin and Cotter piece, in fact, presents two additional figures in direct contrast with the garbage millennial theory – in Monitoring the Future, millennial men’s support for women in the public sphere has plateaued, not fallen; and attitudes about women working have continued to improve, not worsen. Their conclusion is, therefore, that they find some evidence of a move away from gender equality – a nuance that’s since been lost in the discussion of their work.

and Kieran Healy tweeted

 

As a rule if you see survey data (especially on a small subset of the population) without any uncertainty displayed, be suspicious.

Also, it’s impressive how easy these sorts of analysis are with modern technology. They used to require serious computing, expensive software, and potentially some work to access the data.  I did mine in an airport: commodity laptop, free WiFi, free software, user-friendly open-data archive.   One reason that basic statistics training has become much more useful in the past few decades is that so many of the other barriers to DIY analysis have been removed.

Stat of the Week Competition: April 1 – 7 2017

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 April 7 2017.
  • Statistics can be bad, exemplary or fascinating.
  • The statistic must be in the NZ media during the period of April 1 – 7 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…)

March 29, 2017

Technological progress in NZ polling

From a long story at stoppress.co.nz

For the first time ever, Newshub and Reid Research will conduct 25 percent of its polling via the internet. The remaining 75 percent of polling will continue to be collected via landline phone calls, with its sampling size of 1000 respondents and its margin of error of 3.1 percent remaining unchanged. The addition of internet polling—aided by Trace Research and its director Andrew Zhu—will aim to enhance access to 18-35-year-olds, as well as better reflect the declining use of landlines in New Zealand.

This is probably a good thing, not just because it’s getting harder to sample people. Relying on landlines leads people who don’t understand polling to assume that, say, the Greens will do much better in the election than in the polls because their voters are younger. And they don’t.

The downside of polling over the internet is it’s much harder to tell from outside if someone is doing a reasonable job of it. From the position of a Newshub viewer, it may be hard even to distinguish bogus online clicky polls from serious internet-based opinion research. So it’s important that Trace Research gets this right, and that Newshub is careful about describing different sorts of internet surveys.

As Patrick Gower says in the story

“The interpretation of data by the media is crucial. You can have this methodology that we’re using and have it be bang on and perfect, but I could be too loose with the way I analyse and present that data, and all that hard work can be undone by that. So in the end, it comes down to me and the other people who present it.”

It does. And it’s encouraging to see that stated explicitly.

March 28, 2017

Super 18 Predictions for Round 6

Team Ratings for Round 6

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.

Current Rating Rating at Season Start Difference
Hurricanes 17.79 13.22 4.60
Chiefs 10.88 9.75 1.10
Crusaders 8.45 8.75 -0.30
Highlanders 7.61 9.17 -1.60
Lions 7.41 7.64 -0.20
Brumbies 3.71 3.83 -0.10
Stormers 2.36 1.51 0.90
Blues 2.04 -1.07 3.10
Waratahs 1.55 5.81 -4.30
Sharks 0.85 0.42 0.40
Jaguares -1.58 -4.36 2.80
Bulls -2.46 0.29 -2.70
Cheetahs -8.30 -7.36 -0.90
Force -8.57 -9.45 0.90
Reds -9.87 -10.28 0.40
Rebels -11.78 -8.17 -3.60
Kings -17.75 -19.02 1.30
Sunwolves -19.45 -17.76 -1.70

 

Performance So Far

So far there have been 42 matches played, 32 of which were correctly predicted, a success rate of 76.2%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Crusaders vs. Force Mar 24 45 – 17 20.10 TRUE
2 Rebels vs. Waratahs Mar 24 25 – 32 -10.20 TRUE
3 Blues vs. Bulls Mar 25 38 – 14 6.40 TRUE
4 Brumbies vs. Highlanders Mar 25 13 – 18 0.80 FALSE
5 Sunwolves vs. Stormers Mar 25 31 – 44 -18.50 TRUE
6 Kings vs. Lions Mar 25 19 – 42 -21.50 TRUE
7 Cheetahs vs. Sharks Mar 25 30 – 38 -5.30 TRUE
8 Jaguares vs. Reds Mar 25 22 – 8 12.10 TRUE

 

Predictions for Round 6

Here are the predictions for Round 6. 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.

Game Date Winner Prediction
1 Highlanders vs. Rebels Mar 31 Highlanders 23.40
2 Blues vs. Force Apr 01 Blues 14.60
3 Chiefs vs. Bulls Apr 01 Chiefs 17.30
4 Reds vs. Hurricanes Apr 01 Hurricanes -23.70
5 Stormers vs. Cheetahs Apr 01 Stormers 14.20
6 Lions vs. Sharks Apr 01 Lions 10.10
7 Waratahs vs. Crusaders Apr 02 Crusaders -2.90

 

NRL Predictions for Round 5

 

Team Ratings for Round 5

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.

Current Rating Rating at Season Start Difference
Raiders 8.86 9.94 -1.10
Storm 8.13 8.49 -0.40
Sharks 6.61 5.84 0.80
Panthers 5.89 6.08 -0.20
Broncos 5.66 4.36 1.30
Cowboys 4.78 6.90 -2.10
Roosters 2.12 -1.17 3.30
Sea Eagles -0.06 -2.98 2.90
Eels -0.76 -0.81 0.00
Titans -2.90 -0.98 -1.90
Rabbitohs -3.15 -1.82 -1.30
Dragons -3.60 -7.74 4.10
Bulldogs -3.62 -1.34 -2.30
Wests Tigers -6.26 -3.89 -2.40
Warriors -8.03 -6.02 -2.00
Knights -15.71 -16.94 1.20

 

Performance So Far

So far there have been 32 matches played, 18 of which were correctly predicted, a success rate of 56.2%.
Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Rabbitohs vs. Roosters Mar 23 6 – 20 0.50 FALSE
2 Panthers vs. Knights Mar 24 40 – 0 22.30 TRUE
3 Broncos vs. Raiders Mar 24 13 – 12 0.10 TRUE
4 Sea Eagles vs. Bulldogs Mar 25 36 – 0 1.90 TRUE
5 Eels vs. Sharks Mar 25 6 – 20 -2.00 TRUE
6 Titans vs. Cowboys Mar 25 26 – 32 -3.80 TRUE
7 Wests Tigers vs. Storm Mar 26 14 – 22 -11.50 TRUE
8 Dragons vs. Warriors Mar 26 26 – 12 7.30 TRUE

 

Predictions for Round 5

Here are the predictions for Round 5. 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.

Game Date Winner Prediction
1 Bulldogs vs. Broncos Mar 30 Broncos -5.80
2 Roosters vs. Sea Eagles Mar 31 Roosters 5.70
3 Cowboys vs. Rabbitohs Mar 31 Cowboys 11.40
4 Sharks vs. Knights Apr 01 Sharks 25.80
5 Raiders vs. Eels Apr 01 Raiders 13.10
6 Storm vs. Panthers Apr 01 Storm 5.70
7 Warriors vs. Titans Apr 02 Titans -1.10
8 Wests Tigers vs. Dragons Apr 02 Wests Tigers 0.80