Chance News 84
"There's a saying in the San Francisco Bay Area: There are lies, damned lies, and next bus."
Submitted by Jerry Grossman
"Skepticism enjoins scientists — in fact all of us — to suspend belief until strong evidence is forthcoming, but this tentativeness is no match for the certainty of ideologues and seems to suggest to many the absurd idea that all opinions are equally valid. ...What else explains the seemingly equal weight accorded to the statements of entertainers and biological researchers on childhood vaccines?..."
Submitted by Bill Peterson
“Let's start with T. Rowe Price's U.S. stock fund lineup. I have plugged in 15 of its largest actively managed U.S. equity funds. Let's start at the top with T. Rowe Price Blue Chip Growth. Scroll down column 1 and you'll see that T. Rowe Price Growth Stock is a tight fit with a 1.00 correlation--the highest it can get. So, we know that owning those two large-growth funds is rather redundant. Scroll down further and you'll see that Small-Cap Value has the lowest correlation at 0.91--thus, it's a good choice for diversification purposes.”
Morningstar, April 2, 2012
Submitted by Margaret Cibes
“Association Between More Frequent Chocolate Consumption and Lower Body Mass Index”
Archives of Internal Medicine, March 26, 2012
This report (full text not yet available online) was published as a “research letter.” It involved about 1000 Southern Californians, who were surveyed about their eating and drinking habits and whose BMIs were computed. Funded by the National Institutes of Health, the study found that, among this group, people who ate chocolate more frequently had lower BMIs than less frequent chocolate eaters. The authors, in the “research letter” at least, apparently did not claim any cause-and-effect result and indicated that a controlled study would be needed before jumping to any such conclusion.
The Knight Science Journalism Tracker (subtitled “Peer review within science journalism”) presented a nice critique of press accounts of the “research letter” in “Eat Chocolate. Lose Weight. Yeah, right.”.
Before I became aware of the Knight project, I had tracked down a number of press accounts of the study and was encouraged to find it appropriately described in the articles, if not in the headlines, as non-definitive. (This is not to say that all reports were accurate or complete with respect to other aspects of the study.) This might be a good exercise for a stats class, when a similarly enticing topic presents itself in the news, and when the original study report is available for comparison.
(a) The New York Times: “Dietary studies can be unreliable, since so many complicating factors can influence results, and it is difficult to pinpoint cause and effect.”
(b) BBC News: “But the findings only suggest a link - not proof that one factor causes the other.”
(c) TODAY : “The researchers only found an association, not a direct cause-effect link.”
(d) The Times of India: “However, the study's findings may not be taken at face value, as the reasons behind this link between chocolate consumption and weight loss remain unclear.”
(e) Reuters: “Researchers said the findings … don't prove that adding a candy bar to your daily diet will help you shed pounds.”
(f) Poughkeepsie Journal: “The study is limited. It was observational, meaning it analyzed data based on what people said they ate, rather than a controlled trial in which some people are given chocolate and compared with others who receive a placebo.”
(g) The Wall Street Journal: “But before people hoping to lose weight indulge in an extra scoop of chocolate fudge swirl, the researchers caution that the study doesn't prove a link between frequent chocolate munching and weight loss…..”
1. According to Knight, the original purpose of the project was to study “non-cardiac effects on statin drugs,” not chocolate consumption. Should this information have been reported in the articles? Why or why not?
2. Do you think that the size of the chocolate-consuming group was the same as the size of the entire group of respondents? Why would you want to know the “sample” size behind the chocolate results?
3. How would you monitor a controlled study involving a group of people who were instructed to eat chocolate occasionally and another group who were instructed to eat it more frequently?
Submitted by Margaret Cibes