Posts filed under General (3156)

Heavy drinking and the societal harm it causes is a big issue and attracts a lot of media and scholarly attention (and Statschat’s, too). So we were interested to see today’s new release from the Journal of the American Medical Association. It describes a double-blind, parallel-group, individually-randomised trial that studied moderate to heavy student drinkers from seven of our eight universities to see if a web-based alcohol screening and intervention programme reduced their unhealthy drinking behaviour.

And the short answer? Not really. But if they identified as Māori, the answer was … yes, with a caveat. More on that in a moment.

Statistician Nicholas Horton and colleagues used an online questionnaire to identify students at Otago, Auckland, Canterbury, Victoria, Lincoln, Massey, and Waikato who had unhealthy drinking habits. Half the students were assigned at random to receive personalised feedback and the other students had no input. Five months later, researchers followed up with the students on certain aspects of their drinking.

The overall result? “The intervention group tended to have less drinking and fewer problems then the control group, but the effects were relatively modest,” says Professor Horton. The take-away message: A web-based alcohol screening and intervention program had little effect on unhealthy drinking among New Zealand uni students. Restrictions on alcohol availability and promotion are still needed if we really want to tackle alcohol abuse.

But among Māori students, who comprise 10% of our national uni population, those receiving intervention were found to drink 22% less alcohol and to experience 19% fewer alcohol-related academic problems at the five-month follow-up. The paper suggests that Māori students are possibly more heavily influenced by social-norm feedback than non-Māori students. “Māori students may have a stronger group identity, enhanced by being a small minority in the university setting.” But the paper warns that the difference could also be due to chance, “underscoring the need to undertake replication and further studies evaluating web-based alcohol screening and brief intervention in full-scale effectiveness trials.”

The paper is here. Read the JAMA editorial here.

• Extrapolation: According to a US obesity researcher, by 2606 the US diet will be 100% sugar.  And according to Skepchick, we’ll be immortal. He presumably isn’t entirely serious; she totally isn’t.

• From Quartz: The problem with data journalism So here’s a set of ethics that data journalists might follow to avoid common pitfalls:

•  If people already think your data sharing plans are a bit creepy, you do not want to use the phrase “consent fetishists”. Really.

• Data visualisation: summary of  street grid angles in various US cities. The Houston one is a bit misleading because the highways are so dominant in reality but not in the summary.

I had a mistake in my code so that the country assigned to the Sharks was incorrect so the previously posted prediction for the Bulls versus Sharks game was wrongly calculated. I now have the Sharks to win by 0.10 point.

All the other predictions for the round are unchanged.

Team Ratings for Round 6

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 29 matches played, 20 of which were correctly predicted, a success rate of 69%.

Here are the predictions for last week’s games.

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.

Team Ratings for Round 3

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 16 matches played, 6 of which were correctly predicted, a success rate of 37.5%.

Here are the predictions for last week’s games.

Predictions for Round 3

Here are the predictions for Round 3. 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 6

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 29 matches played, 20 of which were correctly predicted, a success rate of 69%.

Here are the predictions for last week’s games.

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.

• Nate Silver’s fivethirtyeight.com is live. He writes about data journalism and what it is
• Also at 538, Jeff Leek (from Simply Statistics) Finally, a Formula For Decoding Health News

• At Pantheon, a visualisation of globally known people over time

• Genetics can shed a lot of light on disease, but not always. Derek Lowe writes about a new study of bipolar disorder, where the genetic associations seem amazingly diverse and inconsistent.

[Update: Just had to add this one from a Huffington Post survey: Nearly a quarter of Americans know what we should do about the Ukraine Administrative Adjustment Act of 2005]

• Your high school transcript will haunt you forever? Partly reasonable, but partly the recurring claim that knowing what works in a given situation will take away your freedom.

• Both men and women think women are bad at math. “Men and women employers alike revealed their prejudice against women for a perceived lack of mathematical ability. When the only information that the employers had was a photograph of the candidate, men were twice as likely to be hired for the simple math job, no matter whether it was a man or woman doing the hiring”. Could do with a lot more scare quotes around words like `employer’, `candidate’, `hired’, but a good report.

• Why Google Trends can’t track the flu (yet) There are lots of differences between flu season and the rest of the year, and the ones most relevant to Google’s ordinary activities don’t have much to do with influenza

• Ok, it’s not statistics as such, but you have to see the mash-up of the Cyclone Lusi animation and Van Gogh’s Starry Night, by @bobsyouruncle

• Cathy at Mathbabe.org on survey questions, pointing out that the sun does too go around the earth.

• Buzzfeed says “According To Pornhub, The South Watches More Gay Porn Than Any Other Part Of The U.S.” The point, for those of you not up on US sociogeography, is that the South is religiously conservative.  It turns out that’s not really what the data say. The figures aren’t % of men who watch gay porn, they are % of porn that is gay male. The data are equally consistent with straight guys in religiously conservative states watching very slightly less porn than those in other states. Data on total porn consumption are mixed.

• ProPublica, the non-profit, public-interest journalism foundation in the US, are setting up a data shop. Data that they could just download, they’ll make available for free, but the data that took a lot of effort will cost. Interesting to see this as a data journalism funding model.

• From ProPublica, a good example of simple arithmetic applied to unreasonable claims.

Since 2009, Dagogo-Jack has been paid at least $257,000 by Glaxo, Lilly and Merck.

“If you actually prorate that by the hours put in, it is barely more than minimum wage,” he said. (A person earning the federal minimum wage of $7.25 would have to work 24 hours a day, seven days a week for more than four years to earn Dagogo-Jack’s fees.)

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

This week I don’t have full details because I have limited internet access and am having to copy the details from my computer.
 

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 5

The basic method is described on my Department home page. I have made some changes to the methodology this year, including shrinking the ratings between seasons.

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 22 matches played, 14 of which were correctly predicted, a success rate of 63.6%.

Here are the predictions for last week’s games.

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.