Posts filed under General (666)

April 23, 2015

Genetic determinism: mosquito bite edition

Q: Did you see that being bitten by mosquitoes is genetic?

A: What? Being outside without mosquito repellent, especially in the evening, is genetic now?

Q: No.

A: Living in places with lots little pools of standing water in the summer is genetic?

Q: No

A: Having wire mesh screens on your windows is genetic?

Q: Ok, yes, very droll. No, “Scientists have found that the chance of being bitten by a mosquito is written in the genes and some people are just more likely to be attacked no matter how much insect repellent they slap on.” What repellent did they use? DEET or one of those lemon things?

A: You mean this paper in PLoS One. They didn’t use any repellent.

Q: So they don’t really know that the usual repellents don’t work for some people because of genetics?

A: No. They didn’t look at that at all.

Q: Should I pretend to be shocked?

A: Don’t bother for now.

Q: Ok, who got bitten by the mosquitoes? You’re not going to tell me it was mice again, are you?

A: No, no mice, but also no bites. The researchers took smell samples from volunteers’ hands, and measured which samples the mosquitoes flew towards?

Q: How did they choose the people?

A: The comparisons were all within sets of female twins.

Q: Not really a representative population sample, was it?

A: It’s a reasonable approach for testing if there’s a genetic component to something: identical twins should be more similar than non-identical twins.

Q: And if it was completely genetic, identical twins would be identical, right?

A: Yes.

Q: So when they say “the mosquitoes would bite none, or both of the identical twins, but the results were mixed for the non-identical twins” that means it was completely genetic?

A:  No, the implication doesn’t work backwards that way. And also that’s a pretty serious exaggeration of what they found.

Q: But at least they did find a genetic component? Some people make a natural repellent?

A: There’s pretty good evidence of a genetic component, even a fairly big one. The article makes it clear that they don’t know whether some people make a repellent or whether other people make an attractant: “It is not known whether the differences between MZ and DZ twins is due to the presence or absence of attractive or repellent chemicals,”

Q: That seems pretty unambiguous, but it isn’t what the newspaper says.

A: No, it isn’t.

Q: Should I pretend to be shocked now?

A: I’d wait and get it over with all at once.

Q: The newspaper has a link to a related story. Should we read that?

A: Sure. Why not?

Q: It says “most of this research uses only one mosquito species. Switch to another species and the results are likely to be different.” Huh. I didn’t know that. Which species did the twin research use?

A: Aedes aegypti, a tropical mosquito (originally from Africa) that spreads yellow fever and dengue.

Q: Is Aedes aegypti common in New Zealand?

A: No, it could live in Northland but the biosecurity folks have stopped it invading so far.

Q: How about in the UK, where the news story came from initially?

A: No, the UK is too cold.

Q: So it’s not really relevant to mosquito bites for their readers?

A: It’s still important as a global health issue, but no, not all that relevant from a mundane viewpoint of actual day-to-day utility.

Q: Ok, is now the time to pretend to be shocked?

A: If it makes you feel better, sure.

 

 

April 22, 2015

Briefly

  • From the BBC: The illusion of control and how it makes us feel better. That’s part of the benefit of real-time transit prediction: knowing how long you have to wait makes you feel more in control, as long as the system is good enough not to shatter the illusion.
  • Social networks to visualise relationships between allegedly-independent landlords

NRL Predictions for Round 8

Team Ratings for Round 8

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
Roosters 8.52 9.09 -0.60
Rabbitohs 8.05 13.06 -5.00
Cowboys 7.76 9.52 -1.80
Storm 5.11 4.36 0.80
Broncos 4.63 4.03 0.60
Warriors 1.75 3.07 -1.30
Panthers 0.77 3.69 -2.90
Dragons 0.35 -1.74 2.10
Bulldogs 0.31 0.21 0.10
Knights -2.28 -0.28 -2.00
Sea Eagles -2.85 2.68 -5.50
Raiders -5.31 -7.09 1.80
Titans -5.36 -8.20 2.80
Sharks -5.85 -10.76 4.90
Eels -6.24 -7.19 0.90
Wests Tigers -8.00 -13.13 5.10

 

Performance So Far

So far there have been 56 matches played, 27 of which were correctly predicted, a success rate of 48.2%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Bulldogs vs. Sea Eagles Apr 17 28 – 16 5.20 TRUE
2 Dragons vs. Broncos Apr 17 12 – 10 -1.90 FALSE
3 Cowboys vs. Warriors Apr 18 28 – 24 11.00 TRUE
4 Storm vs. Roosters Apr 18 17 – 16 -0.70 FALSE
5 Titans vs. Panthers Apr 18 32 – 6 -7.60 FALSE
6 Knights vs. Eels Apr 19 22 – 28 9.10 FALSE
7 Wests Tigers vs. Raiders Apr 19 22 – 30 1.70 FALSE
8 Sharks vs. Rabbitohs Apr 20 18 – 10 -13.90 FALSE

 

Predictions for Round 8

Here are the predictions for Round 8. 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. Wests Tigers Apr 24 Bulldogs 11.30
2 Broncos vs. Eels Apr 25 Broncos 13.90
3 Knights vs. Cowboys Apr 25 Cowboys -7.00
4 Roosters vs. Dragons Apr 25 Roosters 11.20
5 Storm vs. Sea Eagles Apr 25 Storm 11.00
6 Warriors vs. Titans Apr 25 Warriors 11.10
7 Panthers vs. Sharks Apr 26 Panthers 9.60
8 Rabbitohs vs. Raiders Apr 26 Rabbitohs 16.40

 

Super 15 Predictions for Round 11

Team Ratings for Round 11

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
Crusaders 7.84 10.42 -2.60
Waratahs 7.50 10.00 -2.50
Chiefs 5.25 2.23 3.00
Hurricanes 5.18 2.89 2.30
Stormers 3.64 1.68 2.00
Bulls 3.43 2.88 0.60
Brumbies 3.22 2.20 1.00
Highlanders 1.02 -2.54 3.60
Blues 0.15 1.44 -1.30
Sharks -0.50 3.91 -4.40
Lions -3.19 -3.39 0.20
Force -5.75 -4.67 -1.10
Rebels -6.02 -9.53 3.50
Cheetahs -6.71 -5.55 -1.20
Reds -8.08 -4.98 -3.10

 

Performance So Far

So far there have been 66 matches played, 41 of which were correctly predicted, a success rate of 62.1%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Crusaders vs. Chiefs Apr 17 9 – 26 9.50 FALSE
2 Hurricanes vs. Waratahs Apr 18 24 – 29 3.30 FALSE
3 Highlanders vs. Blues Apr 18 30 – 24 4.60 TRUE
4 Brumbies vs. Rebels Apr 18 8 – 13 15.60 FALSE
5 Force vs. Stormers Apr 18 6 – 13 -4.40 TRUE
6 Sharks vs. Bulls Apr 18 10 – 17 1.10 FALSE
7 Cheetahs vs. Reds Apr 18 17 – 18 6.90 FALSE

 

Predictions for Round 11

Here are the predictions for Round 11. 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 Chiefs vs. Force Apr 24 Chiefs 15.50
2 Brumbies vs. Highlanders Apr 24 Brumbies 6.70
3 Crusaders vs. Blues Apr 25 Crusaders 11.70
4 Waratahs vs. Rebels Apr 25 Waratahs 17.50
5 Lions vs. Cheetahs Apr 25 Lions 7.50
6 Stormers vs. Bulls Apr 25 Stormers 4.20
7 Reds vs. Hurricanes Apr 26 Hurricanes -8.80

 

April 15, 2015

Briefly

  • Good article in New York Times about why ‘survival rates’ aren’t the best way to assess progress in cancer. Same explanation that I’ve covered before several times: survival can improve when all you do is move diagnosis earlier without affecting disease or death at all
  • Whether state government subsidy of tuition in the US is increasing or decreasing seems like it should be an easy question. Not so much.
  • Comparing prices from different years without inflation adjustment is like comparing prices from different countries without currency conversion.  Any inflation adjustment is better than none, but if you’re interested in different ways it can be done there’s a fairly comprehensible review by the UK Statistics Authority
  • Headlines based on bogus polls are back. At Stuff, an implausible headline from a survey created to publicise a dating app and National Cheese Week. Celebrate National Library Week instead.
April 12, 2015

Reductionism and the Petone-Grenada link

If you have to make a decision with several options, each with different types of positive and negative effects, it’s going to be hard. Techniques for breaking down complex decisions into sets of simpler questions are very valuable, but it’s important that the way you break down the problem and recombine the answers fits with how you answer the simpler questions.

I’ve been pointed to what looks like an unfortunate example from the NZTA, in assessing options for the Petone–Grenada link road to be constructed near Wellington. The road comes in two sections: from Petone to the eastern section of Lincolnshire Farm, and from there to Grenada. According to the scoping report (PDF), these can be decided independently of each other, so there’s an ideal opportunity to simplify the decision making.  NZTA describes four options P1 to P4 for the first section, and four options A to D for the second section.

I would have expected them to just make independent recommendations for the two sections, but what they actually did was more complicated. First, they looked at the P options and decided based on four criteria that P4 was best.  They then looked at A+P4, B+P4, C+P4, and D+P4 for the same four criteria, and said in a footnote (p172) “Upon combining one of Option P1, P2, P3 or P4 with one Option A, B, C or D the effect more towards the negative takes precedence.

This can only make sense if the harms or benefits weren’t independent.  Sometimes that’s possible. In particular, one of the criteria was “resilience”, and you might argue that it doesn’t matter how robust the second part of the road is when the first part is under several meters of rock and mud, or filled with bumper-to-bumper traffic jams. It could make sense to take the worst value of the two sections when assessing resilience: but people who know more about Wellington-area transport than I do still seem dubious.

The same argument certainly doesn’t apply for the other criteria: archaeological,  ecological,  landscape/visual impact, and transport benefit/cost. If one section of the road is an environmental nightmare, that doesn’t make the environmental impact of the other section unimportant. If one section of the road is unavoidably ugly, that doesn’t excuse making the other section ugly. If one section destroys an important heritage site, it doesn’t mean the other section doesn’t have to care about preservation of the past. If one section is ridiculously expensive it doesn’t mean the costs are unimportant for the other section.

The impact of decomposing and recombining the evaluation as they did, is that any criterion where P4 was bad becomes much less important in choosing among options A to D. P4 was very bad on the landscape/visual criterion, and moderately bad on ecology.

By now you should be expecting the punch line: evaluated independently, options A and B look good because they score well on ecology and landscape/visual criteria. Evaluated in combination with P4, they look terrible, because the ecology and landscape benefits are masked by the “more negative” combining rule. That’s a problem with the combining rule, not with the road. Here’s a colour-coded version of the information in Table 23-19, p182 (from T. Duran)

Separate%20and%20Combined

Not only is the combining rule obviously missing some information, it’s not even internally consistent. If the evaluation had been done in the opposite order they might well have chosen A first, and then looked at A+P1 to A+P4. Even D was what they’d chosen first, P3+D would then look slightly better than P4+D.

It’s very tempting to look for ways of combining preferences that don’t rely on numbers, just on orderings, but in most cases they aren’t available, and attempts to do it leave you worse off than before.

This evaluation wasn’t set up to focus only on resilience — even assuming that the resilience assessment is valid, which I hear is also being questioned — it was set up to value the four criteria equally. It really looks as though a minor detail of the approach to simplifying the evaluation has had a large, accidental effect on the result.

April 10, 2015

Briefly

  • A properly-conducted opinion poll in Cuba, done in secret. Impressive.
  • As the Herald reports, New Zealand moved from 1st to 5th on the index reported by Social Progress Imperative. The story also points out, helpfully, that a lot of this is changes in how things are measured.  It turns out this goes further:  a 2014 version of the index is available using the new measurements. When the same definitions are used for the two years, NZ stays at the same ranking (5th) and improves on the actual values (from 86.93 to 87.08).
  • JPMorgan is using workplace data to predict which employees are likely to ‘go rogue’. Matt Levine doesn’t really worry. The Bloomberg News story worries a bit, but only “Policing intentions can be a slippery slope. Do people get a scarlet letter for something they have yet to do?” They don’t seem to consider false positives: people who weren’t going to do anything wrong (or more wrong than is necessary if you work for an investment bank).
  • The NZ Association of Scientists is having a conference titled “Speaking Out: Going public on difficult issues”. There will probably be more stuff on line soon, but currently you can read an expanded version of Peter Gluckman’s talk, and listen to (NZAS President) Nicola Gaston on Radio NZ; the Twitter hashtag is 
April 8, 2015

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
Rabbitohs 11.30 13.06 -1.80
Roosters 9.06 9.09 -0.00
Cowboys 6.51 9.52 -3.00
Storm 5.32 4.36 1.00
Broncos 4.51 4.03 0.50
Panthers 2.88 3.69 -0.80
Bulldogs 1.52 0.21 1.30
Warriors 1.47 3.07 -1.60
Knights 0.29 -0.28 0.60
Dragons -1.66 -1.74 0.10
Sea Eagles -2.21 2.68 -4.90
Eels -5.31 -7.19 1.90
Raiders -6.34 -7.09 0.70
Wests Tigers -7.54 -13.13 5.60
Sharks -8.87 -10.76 1.90
Titans -9.60 -8.20 -1.40

 

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. Rabbitohs Apr 03 17 – 18 -7.80 TRUE
2 Titans vs. Broncos Apr 03 16 – 26 -11.30 TRUE
3 Knights vs. Dragons Apr 04 0 – 13 7.80 FALSE
4 Sea Eagles vs. Raiders Apr 04 16 – 29 10.30 FALSE
5 Roosters vs. Sharks Apr 05 12 – 20 25.40 FALSE
6 Eels vs. Wests Tigers Apr 06 6 – 22 8.60 FALSE
7 Panthers vs. Cowboys Apr 06 10 – 30 2.40 FALSE
8 Storm vs. Warriors Apr 06 30 – 14 6.50 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 Broncos vs. Roosters Apr 10 Roosters -1.50
2 Sharks vs. Knights Apr 10 Knights -6.20
3 Eels vs. Titans Apr 11 Eels 7.30
4 Panthers vs. Sea Eagles Apr 11 Panthers 8.10
5 Warriors vs. Wests Tigers Apr 11 Warriors 13.00
6 Dragons vs. Bulldogs Apr 12 Bulldogs -0.20
7 Raiders vs. Storm Apr 12 Storm -8.70
8 Rabbitohs vs. Cowboys Apr 13 Rabbitohs 7.80

 

Super 15 Predictions for Round 9

Team Ratings for Round 9

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
Crusaders 10.43 10.42 0.00
Waratahs 8.34 10.00 -1.70
Hurricanes 5.72 2.89 2.80
Brumbies 4.58 2.20 2.40
Chiefs 3.79 2.23 1.60
Bulls 2.49 2.88 -0.40
Stormers 2.03 1.68 0.30
Sharks 0.17 3.91 -3.70
Blues 0.09 1.44 -1.30
Highlanders -0.23 -2.54 2.30
Lions -3.32 -3.39 0.10
Force -4.56 -4.67 0.10
Cheetahs -7.14 -5.55 -1.60
Rebels -7.20 -9.53 2.30
Reds -8.20 -4.98 -3.20

 

Performance So Far

So far there have been 53 matches played, 36 of which were correctly predicted, a success rate of 67.9%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Hurricanes vs. Stormers Apr 03 25 – 20 8.90 TRUE
2 Rebels vs. Reds Apr 03 23 – 15 4.30 TRUE
3 Chiefs vs. Blues Apr 04 23 – 16 7.80 TRUE
4 Brumbies vs. Cheetahs Apr 04 20 – 3 16.00 TRUE
5 Sharks vs. Crusaders Apr 04 10 – 52 -1.60 TRUE
6 Lions vs. Bulls Apr 04 22 – 18 -2.70 FALSE

 

Predictions for Round 9

Here are the predictions for Round 9. 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 Blues vs. Brumbies Apr 10 Blues 0.00
2 Crusaders vs. Highlanders Apr 11 Crusaders 14.70
3 Waratahs vs. Stormers Apr 11 Waratahs 10.80
4 Force vs. Cheetahs Apr 11 Force 7.10
5 Bulls vs. Reds Apr 11 Bulls 15.20
6 Lions vs. Sharks Apr 11 Lions 0.50

 

April 7, 2015

Briefly

  • NPR’s Science Friday covers BAHfest, a competition to produce what look like scientific arguments for nutty conclusions. Hilarious, but also important: serious and scammy pseudoscience uses the same tricks.
  • Emma Pierson, a scientist who studies dating analyses a year of emails with her boyfriend
    Him
    : You’re going to find some weird pattern and break up with me.

    Me: Either that will be warranted by the data, in which case it’s a good thing, or it won’t, in which case I’m a bad statistician. Are you saying I’m a bad statistician?

  • And a post by Emma Pierson at 538.com: “people just want to date themselves”
  • Another story about changes in cancer risk that just uses number of diagnoses, without even gesturing in the direction of screening bias.