Posts filed under General (680)

May 21, 2015

Briefly

  • Sometimes people with an axe to grind are right. In this case the people who cast aspersions on the leading data-based research opposing same-sex parenting. The closer they look at the data, the less convincing it is. (NY Magazine, new research paper) “The reanalysis illustrates the importance of methodological decisions in research”
  • A study of spreadsheets in their natural habitat: blog post, paper by Felienne Harmans
  • Facetted barcharts and fluctuation diagrams, from Di Cook. The data describes the responses of couples on questions about their sex life.
  • Looking at scientists giving advice on politically controversial topics: a case study of badger culling in the UK by Helen Briggs. “The badgers moved the goalposts”
  • From the New Zealand conference ‘Going Public,’ on the same topic, a post by Dr SM Morgan , who works on health literacy. “Find something complementary to say about a scientific colleague’s scicomm efforts and imagine saying it out loud to their face.”
May 20, 2015

Actually it’s about neuroscience in videogame journalism

Q: Why does Stuff think playing ‘Call of Duty’ increases the risk of Alzheimer’s disease? I didn’t think old people played violent video games much.

A: I don’t think Stuff does think anything in particular about it. They just reprinted that from the Telegraph and trimmed out the casual sexism.

Q: Ok, why does the Telegraph think playing ‘Call of Duty’ increases the risk of Alzheimer’s disease? I didn’t think old people played violent video games much.

A: It’s not so much about the games they play now as the ones they played 60 years earlier

Q: What video games did they play 60 years ago?

A: Not current people with Alzheimer’s; gamers now who might get Alzheimer’s in a few decades.

Q: Ok, so why will that happen?

A: Because video game players use response learning strategies for navigation in video mazes

Q: Why is that bad?

A: Because other research found people who used those strategies had more activity in their caudate nucleus.

Q: Is this going to start making sense soon?

A:. Yes. Sorry. The research found that when navigating a virtual-reality maze habitual game players used strategies that had previously been correlated with less activity in a part of the brain involved in memory and spatial awareness than normal people did. They apparently used different strategies involving other parts of the brain.

Q: And why is this a problem?

A: Because that part of the brain, the hippocampus, is less active in people with Alzheimer’s, as well as some other neurological and psychological disorders

Q: While they’re playing video games?

A: No, all the time.

Q: Couldn’t it just be that the video gamers have developed a more efficient strategy and that their hippocampuses are perfectly fine. Or hippocampi, whatever?

A: Yes, that could also be the case.

Q: I mean, if you saw people twitching their thumbs rapidly playing a video game it would be fine, but if they were just doing that while sitting around at meetings you’d worry a bit.

A: Indeed.

Q: Did the research look at memory or cognition at all?

A: No.

Q: Do they even know that these brain differences happened after playing video games? Could it be that people who don’t use that part of the brain for video navigation are just better at games?

A: It could be, yes.

Q: The story quotes the percentages using the parts of their brain to four significant digits. Does that mean there were tens of thousands of people in the research?

A: No.

Q: How many?

A: 59: about 30 in each group

Q: If this was true, could it explain why dementia is increasingly common?

A: No.

Q: Why not?

A: Partly because it’s too soon, and partly because dementia isn’t increasingly common at a given age, at least in the US and Europe. If anything, it’s less common. There are more cases now because there are more old people.

Q: It sounds like more research might be needed before writing international headlines about the risk of a terrifying disease.

A: You think?

NRL 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
Roosters 9.18 9.09 0.10
Cowboys 7.37 9.52 -2.20
Rabbitohs 6.05 13.06 -7.00
Storm 5.13 4.36 0.80
Broncos 3.81 4.03 -0.20
Dragons 2.04 -1.74 3.80
Panthers 1.01 3.69 -2.70
Warriors 0.85 3.07 -2.20
Knights -1.67 -0.28 -1.40
Raiders -1.82 -7.09 5.30
Sea Eagles -2.10 2.68 -4.80
Bulldogs -2.14 0.21 -2.30
Sharks -5.61 -10.76 5.10
Eels -6.88 -7.19 0.30
Wests Tigers -6.90 -13.13 6.20
Titans -6.97 -8.20 1.20

 

Performance So Far

So far there have been 80 matches played, 44 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. Roosters May 15 10 – 24 -7.30 TRUE
2 Cowboys vs. Broncos May 15 31 – 20 5.80 TRUE
3 Eels vs. Warriors May 16 13 – 17 -3.70 TRUE
4 Storm vs. Rabbitohs May 16 16 – 12 1.70 TRUE
5 Titans vs. Sharks May 16 22 – 23 2.10 FALSE
6 Dragons vs. Raiders May 17 32 – 18 5.70 TRUE
7 Knights vs. Wests Tigers May 17 22 – 12 7.90 TRUE
8 Sea Eagles vs. Panthers May 18 10 – 11 0.10 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 Rabbitohs vs. Eels May 22 Rabbitohs 15.90
2 Wests Tigers vs. Cowboys May 23 Cowboys -11.30
3 Raiders vs. Bulldogs May 24 Raiders 3.30
4 Knights vs. Broncos May 25 Broncos -2.50

 

Super 15 Predictions for Round 15

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.

Current Rating Rating at Season Start Difference
Crusaders 8.89 10.42 -1.50
Waratahs 6.20 10.00 -3.80
Hurricanes 5.54 2.89 2.60
Chiefs 4.44 2.23 2.20
Brumbies 4.16 2.20 2.00
Highlanders 2.77 -2.54 5.30
Bulls 2.73 2.88 -0.10
Stormers 2.35 1.68 0.70
Blues -0.44 1.44 -1.90
Sharks -1.94 3.91 -5.90
Lions -3.00 -3.39 0.40
Rebels -4.59 -9.53 4.90
Force -4.80 -4.67 -0.10
Cheetahs -6.69 -5.55 -1.10
Reds -8.61 -4.98 -3.60

 

Performance So Far

So far there have been 92 matches played, 60 of which were correctly predicted, a success rate of 65.2%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Blues vs. Bulls May 15 23 – 18 0.70 TRUE
2 Reds vs. Rebels May 15 46 – 29 -2.20 FALSE
3 Hurricanes vs. Chiefs May 16 22 – 18 5.30 TRUE
4 Waratahs vs. Sharks May 16 33 – 18 12.10 TRUE
5 Lions vs. Brumbies May 16 20 – 30 -1.60 TRUE
6 Cheetahs vs. Highlanders May 16 24 – 45 -2.90 TRUE

 

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.

Game Date Winner Prediction
1 Chiefs vs. Bulls May 22 Chiefs 6.20
2 Reds vs. Sharks May 22 Sharks -2.20
3 Blues vs. Hurricanes May 23 Hurricanes -2.00
4 Waratahs vs. Crusaders May 23 Waratahs 1.80
5 Force vs. Highlanders May 23 Highlanders -3.10
6 Cheetahs vs. Lions May 23 Cheetahs 0.30
7 Stormers vs. Rebels May 23 Stormers 11.40

 

Weather uncertainty

From the MetService warnings page

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The ‘confidence’ levels are given numerically on the webpage as 1 in 5 for ‘Low’, 2 in 5 for ‘Moderate’ and 3 in 5 for ‘High’. I don’t know how well calibrated these are, but it’s a sensible way of indicating uncertainty.  I think the hand-drawn look of the map also helps emphasise the imprecision of forecasts.

(via Cate Macinnis-Ng on Twitter)

May 13, 2015

NRL Predictions for Round 10

Team Ratings for Round 10

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 8.69 9.09 -0.40
Cowboys 6.99 9.52 -2.50
Rabbitohs 6.22 13.06 -6.80
Storm 4.95 4.36 0.60
Broncos 4.20 4.03 0.20
Dragons 1.44 -1.74 3.20
Panthers 0.93 3.69 -2.80
Warriors 0.82 3.07 -2.30
Raiders -1.22 -7.09 5.90
Bulldogs -1.66 0.21 -1.90
Knights -1.83 -0.28 -1.60
Sea Eagles -2.02 2.68 -4.70
Sharks -5.85 -10.76 4.90
Titans -6.74 -8.20 1.50
Wests Tigers -6.74 -13.13 6.40
Eels -6.85 -7.19 0.30

 

Performance So Far

So far there have been 72 matches played, 38 of which were correctly predicted, a success rate of 52.8%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Broncos vs. Panthers May 08 8 – 5 6.80 TRUE
2 Roosters vs. Wests Tigers May 08 36 – 4 16.20 TRUE
3 Cowboys vs. Bulldogs May 09 23 – 16 12.40 TRUE
4 Raiders vs. Titans May 09 56 – 16 3.70 TRUE
5 Sharks vs. Warriors May 09 16 – 20 -2.40 TRUE
6 Eels vs. Storm May 10 10 – 28 -7.30 TRUE
7 Sea Eagles vs. Knights May 10 30 – 28 3.00 TRUE
8 Rabbitohs vs. Dragons May 11 16 – 10 8.10 TRUE

 

Predictions for Round 10

Here are the predictions for Round 10. 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. Roosters May 15 Roosters -7.30
2 Cowboys vs. Broncos May 15 Cowboys 5.80
3 Eels vs. Warriors May 16 Warriors -3.70
4 Storm vs. Rabbitohs May 16 Storm 1.70
5 Titans vs. Sharks May 16 Titans 2.10
6 Dragons vs. Raiders May 17 Dragons 5.70
7 Knights vs. Wests Tigers May 17 Knights 7.90
8 Sea Eagles vs. Panthers May 18 Sea Eagles 0.10

 

Super 15 Predictions for Round 14

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.

Current Rating Rating at Season Start Difference
Crusaders 8.89 10.42 -1.50
Waratahs 5.94 10.00 -4.10
Hurricanes 5.66 2.89 2.80
Chiefs 4.32 2.23 2.10
Brumbies 3.60 2.20 1.40
Bulls 3.04 2.88 0.20
Stormers 2.35 1.68 0.70
Highlanders 1.72 -2.54 4.30
Blues -0.75 1.44 -2.20
Sharks -1.68 3.91 -5.60
Lions -2.45 -3.39 0.90
Rebels -3.48 -9.53 6.00
Force -4.80 -4.67 -0.10
Cheetahs -5.64 -5.55 -0.10
Reds -9.72 -4.98 -4.70

 

Performance So Far

So far there have been 86 matches played, 55 of which were correctly predicted, a success rate of 64%.

Here are the predictions for last week’s games.

Game Date Score Prediction Correct
1 Crusaders vs. Reds May 08 58 – 17 20.80 TRUE
2 Rebels vs. Blues May 08 42 – 22 -0.60 FALSE
3 Hurricanes vs. Sharks May 09 32 – 24 12.50 TRUE
4 Force vs. Waratahs May 09 18 – 11 -8.60 FALSE
5 Lions vs. Highlanders May 09 28 – 23 -0.40 FALSE
6 Stormers vs. Brumbies May 09 25 – 24 3.70 TRUE

 

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.

Game Date Winner Prediction
1 Blues vs. Bulls May 15 Blues 0.70
2 Reds vs. Rebels May 15 Rebels -2.20
3 Hurricanes vs. Chiefs May 16 Hurricanes 5.30
4 Waratahs vs. Sharks May 16 Waratahs 12.10
5 Lions vs. Brumbies May 16 Brumbies -1.60
6 Cheetahs vs. Highlanders May 16 Highlanders -2.90

 

Briefly

  • Rating systems are the popular way to scale ‘reputation’ statistically so it works for internet transactions between people who don’t know each other. Tom Slee has a couple of pieces (via Cosma Shalizi): Some Obvious Things About Internet Reputation Systems  and In praise of fake reviews:So the reviews that a restaurant owner believes are most likely to be fair are precisely the ones that Yelp judges to be untrustworthy….Unfortunately for restaurateurs, their opinions on trustworthy reviews are irrelevant. The company is not legally bound to be fair in its filtering and sorting activities,
  • Another example of interesting results failing to replicate, this time from a popular TED talk about posture. As the post at Data Colada points out, this is a strong non-replication: it’s not just that they didn’t see they effect, they ruled out even much weaker effects. There’s a reason statisticians go on and on about over-interpretation of single, small studies.
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  • Looking at the Census data on religion, a map and set of stories from Lincoln Tan and Harkanwal Singh at the Herald
  • A rather different form of data journalism, reported at Buzzfeed (or the original paper report here). The Telegraph had a ‘tactical voting tool’ that said who you should vote for if your goal was a Labour or Tory government.  It was mostly honest, despite the paper’s well-known preferences. However, as Buzzfeed’s headline says: “The Telegraph’s Tactical Voting Tool Was Coded To Never Recommend The SNP”
  • From the LA Times, Wylie Burke on “Why whole-genome testing hurts more than it helps” (disclosure: I once co-supervised a student with Prof Burke)
  • A Slate article by a lawyer says Wyoming has ‘criminalized citizen science’ by creating a law against collecting and reporting environmental data. Now, Wyoming has created crimes of “unlawful collection of resource data” and “trespassing to unlawfully collect resource data”, but I’m pretty sure the Slate article exaggerates them.  “Unlawful collection” can only happen on private land, which the article clearly gets wrong. “Trespassing to unlawfully collect” can happen on public land, but I’m not convinced that in the National Park example there isn’t the necessary authorisation to enter the land. Presumably the law does something or they wouldn’t have bothered passing it, and it’s probably something evil, but a better article would have been nice.
May 10, 2015

The problem with medical progress

Stuff says:

There has been an alarming upward trend in the costs of similar treatments, as more drugs are developed and come on to the market, new Pharmac figures show.

I would argue that this is almost precisely not the problem. The story covers two important issues, but doesn’t distinguish them well.

The first issue is that many expensive new drugs aren’t very good. To get a drug approved for marketing you don’t need to show it’s better than the current stuff, and it often isn’t. Similar treatments might still be useful to have, if they give other options for people with side effects or have more convenient dosing, but they are often more expensive.

The United States is very bad at not using treatments that are similar (or worse) but more expensive, so these drugs are a problem there. Here, we’re quite good at not using them, so they don’t matter all that much. As long as Pharmac enjoys popular support and the media doesn’t buy into too many drug-industry publicity campaigns, we can ignore the expensive new drugs that aren’t worth the cost.

A second issue is that a subset of the expensive new drugs aren’t similar. The story quotes the price differences for ‘anthracycline’ (doxorubicin or epirubicin) and two newer breast cancer drugs, docetaxel and trastuzumab, as evidence of increases over the years.

Anthracyclines haven’t gone away. In fact, they’re quite a bit less expensive now than they were in 2002. The reason Pharmac now buys docetaxel and trastuzumab is that they’re worth the extra cost for at least some women. The existence of trastuzumab is not a problem for the healthcare system, it’s an opportunity.

There is a problem coming, though: many of the new drugs have names ending in ‘mab’.

Monoclonal antibodies, ‘mab’s, are one of the classes of ‘biologics': big, complex molecules made by living cells. Making and testing generic versions of biologics (called ‘biosimilars‘) is much harder than running up off-brand doxorubicin. Even when the patents run out on the ‘mab’s and ‘ept’s, a competitive market might be a while in developing and prices will stay higher.  It’s not so much the expensive on-patent drugs that are a worrying change, it’s the prospect of expensive off-patent drugs in the future.

 

May 9, 2015

Briefly

  • Nate Silver Ben Lauderdale carefully examines how his predictions (and everyone else’s) were so staggeringly wrong in the UK election. More people should do this sort of thing.
  • So, in a different way, did Tom Katsumi
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  • There’s a US court case on whether FDA restrictions on ‘off-label’ drug advertising (ie, advertising a drug for uses it hasn’t been approved for) violates the 1st Amendment. There’s a definite chance the FDA will lose, which would strengthen the incentives to find new uses for drugs, but weaken the incentives to collect good evidence that the drug is actually effective for these uses.
  • Just over half of Tindr users are single, but that’s ok because the company “never intended it to be a dating platform.” Maybe people are just using it for the articles.
  • How lucky do you have to be for it to be evidence of insider trading? Especially when you consider what some traders will call a “once in 3 billion years” event. What isn’t mentioned here but is important is the idea of likelihood ratios: we’re not just looking at whether an event is unlikely, but whether it becomes much more likely under the alternative hypothesis that you’ve got an inside source.
  • Player characters in role-playing games accept unreasonable risks:
    Someone, we’ll call that person the Game Master, wants you to accept a single D8 die roll, with death no resurrection on a 1. But as a sweetener, if you roll 2-8 you’ll get…something nice! What would the something nice have to be for you to agree to make that roll?