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Question 6 of my final exam for Design and Analysis of Sample Surveys

6. A survey of New York City residents is performed using cluster sampling. The design effect is 3.0. From the survey, the estimated proportion who prefer the Mets to the Yankees is 0.42 with a standard error of 0.05. How many people were in the sample?

Solution to question 5

From yesterday:

5. Which of the following better describes changes in public opinion on most issues? (Choose only one.)

(a) Dynamic stability: On any given issue, average opinion remains stable but liberals and conservatives move back and forth in opposite directions (the “accordion model”)

(b) Uniform swing: Average opinion on an issue can move but the liberals and conservatives don’t move much relative to each other (the disribution of opinions is a “solid block of wood”)

(c) Compensating tradeoffs: When considering multiple survey questions on the same general topic, average opinion can move sharply to the left or right on individual questions while the average over all the questions remains stable (the “rubber band model”)

Solution: b. You can make an argument for option a over the long term, but if you have to pick just one of the three, you have to go with uniform swing.

Wikipedia author confronts Ed Wegman

Wegman: “It’s not reprinted 100 percent like you had it.”

Wikipedia guy: “No, you added another paragraph at the end and you changed the headline. . . . You even copied the typos that I’ve corrected on my website. It was taken verbatim and reprinted in your paper.”

The original author got a check for $500 but, unfortunately, no free subscription to “Wiley Interdisciplinary Reviews: Computational Statistics” (a $1400-$2800 value).

P.S. To those who think I’m being mean to Wegman: I haven’t yet heard that he’s apologized to the people whose work he copied without attribution, or to the people who spent their time tracking all this down, or to the U.S. Congress for misrepresenting his expertise in his official report.

Everyone makes mistakes, and just about everyone has ethical lapses at times. But when you get caught you’re supposed to make apology and restitution.

Question 5 of my final exam for Design and Analysis of Sample Surveys

5. Which of the following better describes changes in public opinion on most issues? (Choose only one.)

(a) Dynamic stability: On any given issue, average opinion remains stable but liberals and conservatives move back and forth in opposite directions (the “accordion model”)

(b) Uniform swing: Average opinion on an issue can move but the liberals and conservatives don’t move much relative to each other (the disribution of opinions is a “solid block of wood”)

(c) Compensating tradeoffs: When considering multiple survey questions on the same general topic, average opinion can move sharply to the left or right on individual questions while the average over all the questions remains stable (the “rubber band model”)

Solution to question 4

From yesterday:

4. Researchers have found that survey respondents overreport church attendance. Thus, naive estimates from surveys overstate the percentage of Americans who attend church regularly. Does this have a large impact on estimates of time trends in religious attendance?

Solution: Yes. See this article by Hadaway, Marler, and Chaves, who write, “We suspect that the actual attendance rate has declined since World War II, despite the fact that the survey rate remained basically stable.”

A statistical research project: Weeding out the fraudulent citations

John Mashey points me to a blog post by Phil Davis on “the emergence of a citation cartel.” Davis tells the story:
Continue reading ‘A statistical research project: Weeding out the fraudulent citations’ »

Question 4 of my final exam for Design and Analysis of Sample Surveys

4. Researchers have found that survey respondents overreport church attendance. Thus, naive estimates from surveys overstate the percentage of Americans who attend church regularly. Does this have a large impact on estimates of time trends in religious attendance?

Solution to question 3

From yesterday:

3. We discussed in class the best currently available method for estimating the proportion of military servicemembers who are gay. What is that method? (Recall the problems with the direct approach: there is no simple way to survey servicemembers at random, nor is it likely that they would answer such a question honestly.)

Solution: I was talking about the work of Gary Gates, combining an estimate of the percentage of gays in the population with an estimate of the probability that someone is in the military, given that he or she is gay.

I hate to get all Gerd Gigerenzer on you here, but . . .

Jonathan Cantor points me to an opinion piece by psychologist Reid Hastie, “Our Gift for Good Stories Blinds Us to the Truth.”

I have mixed feelings about Hastie’s article. On one hand I do think his point is important. It’s not new to me, but presumably it’s new to many readers of bloomberg.com. I like Hastie’s book (with Robyn Dawes), Rational Choice in an Uncertain World, and I’m predisposed to like anything new that he writes.

On the other hand, there’s something about Hastie’s article that bothered me. It seemed a bit smug, as if he thinks he understands the world and wants to just explain it to the rest of us. That could be fine—after all, Hastie is a distinguished psychology researcher—but I wasn’t so clear that he’s so clear on what he’s saying. For example:

The human brain is designed to support two modes of thought: visual and narrative. These forms of thinking are universal across human societies throughout history, develop reliably early in individuals’ lives, and are associated with specialized regions of the brain.

Is that really true? How does math fit into this picture? Or music? Music has a sort of narrative structure but it doesn’t seem quite like a story, either.

Hastie continues:

What isn’t universal or natural is the kind of highly structured cognitive processes that underlie logical and mathematical thinking.

Not natural . . . really? Maybe math is not universal, but certainly it’s natural. I was doing it when I was 2 years old. And music, that does seem to be universal, no?

Later on:

The mathematics of causal reasoning has recently experienced a major change, with the widespread acceptance of Bayesian Causal Networks as a normative, rational model for causal induction and reasoning.

Ummm . . . maybe Hastie is a bit too accepting of this particular story! I think Bayesian inference is great—I wrote two books on the topic!—but I wouldn’t go so far as to call it “a normative, rational model for causal induction and reasoning.” But I suppose that if I feel able to opine about psychology, I can’t object to Hastie expressing his views on statistics.

Hastie continues with a famous example:

The legendary theorists of decision-making Amos Tversky and Daniel Kahneman illustrated [our desire for stories] with the following pair of judgment questions: One group of respondents was asked, “What is the probability that a massive flood will occur sometime in the next year and drown more than 1,000 Americans?” The typical estimate was low (less than 20 percent). But, when another comparable sample of respondents was asked, “What is the probability that an earthquake in California will be followed by a flood in the next year that drowns at least 1,000 Americans?” the estimates were significantly higher.

The irrationality is that the second question is about a much more specific event, an earthquake that would be only one of the several reasons for the flood referred to in the first question. It is logically impossible for the second probability to be higher than the first. But, because the second question provides a plausible scenario for the unlikely outcome in the first query, our innate preference for a good story trumps our logical thinking skills.

This story is a great example of the availability heuristic, but I don’t see how it demonstrates a problem with “our logical thinking skills.” When responding to the first question, many people have difficulty visualizing that massive flood. The second question gives a clue. But I don’t see the combination of responses (coming from different sets of people) as indicating irrationality. Most people are not flood experts. They answer the questions as best they can, and when you give more information they will use it.

I hate to get all Gerd Gigerenzer on you here, but what’s the point of saying that this “trumps our logical thinking skills”? I think Kahneman and Tversky did better, decades ago, by writing of “heuristics and biases.”

What’s the political message here?

The article under discussion concludes with:

So the next time you hear a good story about why the financial recession, or any other economically significant event, was caused by a single collection of bad actors — or how a simple linear narrative “explains” an important event — remember this: Just as we are wired to like a diet rich in fats and sugars, we have an appetite for simple, coherent narratives. Neither habit is good for our long-term health.

(Reid Hastie, a professor of behavioral science at the University of Chicago Booth School of Business, is a contributor to Business Class. The opinions expressed are his own.)

Aaahhhh, now I get the message: The financial crisis is nobody’s fault! Let’s put aside the politics of blame, let’s all work together etc etc. OK, fine. Does this apply to all catastrophes? If you know someone in a plane that crashed, are we allowed to check if the pilot was stoned before takeoff? If someone takes $100,000 from you on a fraudulent pretext, and you catch him, are you allowed to try to collect? Or is it only in the financial crisis that we should set aside all “good stories” and “simple linear narratives”?

I agree that our financial problems our complex, and I’m all for warning people about the simplicity of storytelling, but I’m also a bit suspicious of someone from the University of Chicago School of Business telling me not to think about stories of the financial crisis.

Getting quantitative

Also, I’m surprised that, when people estimate “the probability that a massive flood will occur sometime in the next year and drown more than 1,000 Americans” as less than 20%, Hastie characterizes that estimate as “low.” Even Katrina drowned only 387 people (according to this source which I found by googling Katrina drownings). If a 20% chance of this “massive flood” occurring in a one-year period is “low,” I’d be interested in what Hastie thinks is a more reasonable probability estimate.

Responding

Hastie’s article bothered me for two reasons. First, what does it mean to it describe “the kind of highly structured cognitive processes that underlie logical and mathematical thinking” as “unnatural.” I don’t quite get what “natural” means here.

Second, I see an implicit political message, which seems to be that we shouldn’t blame anyone for the financial crisis:

We know there was no single cause or event that set in motion the crisis and that the truth is complex and multicausal. So why do we keep seeking the easy answers? It may be that we are hard-wired to do so.

Or, as the guy said in Repo Man, “it’s society’s fault.”

I contacted bloomberg.com, the publishers of the above-linked article, but was told:

We typically don’t publish opeds responding to articles we’ve published, though we welcome letters to the editor. We also post corrections to pieces containing factual errors and would gladly review any objections you have to Mr. Hastie’s column.

Fair enough, but in this case I don’t think the problems would be resolved by a correction note. I’m more bothered by the totality of the piece. For example, the claim that logical reasoning is “unnatural” is not quite a “factual error” but it still seems wrong to me.

P.S. Someone who knows the judgment and decision making field better than I do writes:

I don’t think that Reid has a political agenda here. (He has only been at Chicago for a few years, and Chicago’s School of Business is not monolithic.) . . . To say that blame narratives are oversimplified is not the same as saying that nobody should be blamed; you may be reading the latter subtext into his text.

So maybe I was being unfair. Although I’d feel a little better about Hastie’s column if he’d clarified that, even though stories can be oversimplified, the “life is complicated” defense shouldn’t be used to get people off the hook.

Also, I’m still unhappy about the claim that logical and mathematical reasoning is “unnatural.” But this fits with the innumeracy of thinking there’s a greater-than-20%-chance of a major flood in any given year. I feel that, to Hastie, numbers are just words. Which is consistent with the idea that mathematical reasoning is unnatural to him.

Question 3 of my final exam for Design and Analysis of Sample Surveys

3. We discussed in class the best currently available method for estimating the proportion of military servicemembers who are gay. What is that method? (Recall the problems with the direct approach: there is no simple way to survey servicemembers at random, nor is it likely that they would answer such a question honestly.)

Solution to question 2

From yesterday:

2. Which of the following are useful goals in a pilot study? (Indicate all that apply.)

(a) You can search for statistical significance, then from that decide what to look for in a confirmatory analysis of your full dataset.

(b) You can see if you find statistical significance in a pre-chosen comparison of interest.

(c) You can examine the direction (positive or negative, even if not statistically significant) of comparisons of interest.

(d) With a small sample size, you cannot hope to learn anything conclusive, but you can get a crude estimate of effect size and standard deviation which will be useful in a power analysis to help you decide how large your full study needs to be.

(e) You can talk with survey respondents and get a sense of how they perceived your questions.

(f) You get a chance to learn about practical difficulties with sampling, nonresponse, and question wording.

(g) You can check if your sample is approximately representative of your population.

Solution: e and f. The purpose of a pilot study is to test out the data collection. The sample size will be too small for a, b, c, d, and g. In some of their earliest work, Kahneman and Tversky documented the common misconception of researchers that data from a small pilot study should closely match the population.

The question would have clearer if I’d inserted the word “small” before “pilot” in the preamble.

Stolen jokes

Fun stories here (from Kliph Nesteroff, link from Mark Palko).

More on Uncle Woody

Here.

See also here. He did Wacky Packs!

Question 2 of my final exam for Design and Analysis of Sample Surveys

2. Which of the following are useful goals in a pilot study? (Indicate all that apply.)

(a) You can search for statistical significance, then from that decide what to look for in a confirmatory analysis of your full dataset.

(b) You can see if you find statistical significance in a pre-chosen comparison of interest.

(c) You can examine the direction (positive or negative, even if not statistically significant) of comparisons of interest.

(d) With a small sample size, you cannot hope to learn anything conclusive, but you can get a crude estimate of effect size and standard deviation which will be useful in a power analysis to help you decide how large your full study needs to be.

(e) You can talk with survey respondents and get a sense of how they perceived your questions.

(f) You get a chance to learn about practical difficulties with sampling, nonresponse, and question wording.

(g) You can check if your sample is approximately representative of your population.

Solution to question 1

From yesterday:

1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.)

Solution: Draw the probability tree, you get that the proportion of people who say they voted is .3+.7p. Solve .3+.7p=.4, you get p=(.4-.3)/.7=.14, or 14%. I was also going to ask for the standard error (which you’d obtain by starting with the standard error for the “.4″ and propagating that through) but I decided to keep it simple. As it was, only about half the students got this question right. This is not a knock on the kids—I just didn’t teach this material well—I’m just letting you know to give a sense that this isn’t such an easy problem.

P.S. As some commenters note, Problem 1 isn’t so realistic. Commenter awm points out that “for the most part people aren’t lying and that the sorts of people who participate in surveys about elections are disproportionately the sort of people who vote.” My problem would’ve been cleaner if I’d also said to assume there was no nonresponse, and if I’d chosen a better example!

black and Black, white and White

I’ve always thought it looked strange to see people referred to in print as Black or White rather than black or white. For example consider this sentence: “A black guy was walking down the street and he saw a bunch of white guys standing around.” That looks fine, whereas “A Black guy was walking down the street and he saw a bunch of White guys standing around”—that looks weird to me, as if the encounter was taking place in an Ethnic Studies seminar.

But maybe I’m wrong on this. Jay Livingston argues that black and white are colors whereas Black and White are races (or, as I would prefer to say, ethnic categories) and illustrates with this picture of a white person and a White person:

In conversation, I sometimes talk about pink people, brown people, and tan people, but that won’t work in a research paper.

P.S. I suspect Carp will argue that I’m being naive: meanings of words change across contexts and over time. To which I reply: Sure, but I still have to choose how to write these words!

Question 1 of my final exam for Design and Analysis of Sample Surveys

1. Suppose that, in a survey of 1000 people in a state, 400 say they voted in a recent primary election. Actually, though, the voter turnout was only 30%. Give an estimate of the probability that a nonvoter will falsely state that he or she voted. (Assume that all voters honestly report that they voted.)

P.S. The commenters are picking up some of the unintended “Hare and pineapple” ambiguity in my question!

Are our referencing errors undermining our scholarship and credibility? The case of expatriate failure rates

Thomas Basbøll points to this ten-year-old article from Anne-Wil Harzing on the consequences of sloppy citations. Harzing tells the story of an unsupported claim that is contradicted by published data but has been presented as fact in a particular area of the academic literature. She writes that “high expatriate failure rates [with "expatriate failure" defined as "the expatriate returning home before his/her contractual period of employment abroad expires"] were in fact a myth created by massive misquotations and careless copying of references.” Many papers claimed an expatriate failure rate of 25-40% (according to Harzing, this is much higher than the actual rate as estimated from empirical data), with this overly-high rate supported by a complicated link of references leading to . . . no real data.

Hartzing reports the following published claims:

Harvey (1996: 103): `The rate of failure of expatriate managers relocating overseas from United States based MNCs has been estimated to range between 25±40 per cent (Tung, 1982, 1988; Mendenhall and Oddou, 1985; Gray 1991; Wedersphan, 1992; Solomon, 1994; Dowling, Schuler and Welch, 1994; Swaak, 1995).’
Shay and Bruce (1997: 30): `Cross-industry studies have estimated US expatriate failure, defined as premature return from an overseas assignment, at between 25±40 per cent for developed countries (Baker and Ivancevich, 1971; Tung, 1981).’

Ashamalla (1998: 54): `According to a number of recent [emphasis added] studies, the rate of failure among American expatriates ranges from 25 to 40 per cent depending on the location of the assignment (Dumaine, Fortune, 1995; McDonald, 1993; Ralston et al., 1995).’

Hartzing writes that, despite the profusion of references which appear to show multiple confirmations, these claims all comes from a single publication from 1979 which itself gives no source for its numbers.

If you believe Hartzing on this (and I see no reason not to), this is not about one or two sloppy researchers; rather, it seems to be general practice for people to thrown in citations without reading the original articles, thus creating a statistical problem of increasing the apparent N by treating multiple instances of the same claim as if they were independent pieces of supporting evidence.

My final exam for Design and Analysis of Sample Surveys

We had 28 class periods, so I wrote an exam with an approximate correspondence of one question per class. Rather than dumping the exam in your lap all at once, I’ll post the questions once per day. Then each day I’ll post the answer to yesterday’s questions. So it will be 29 days in all. I’ll post them to appear late in the day so as not to interfere with our main daily posts (which are currently backed up to early June).

The course was offered in the political science department and covered a mix of statistical and political topics. Followers of our recent discussion on test questions won’t be surprised to learn that some of the questions are ambiguous. This wasn’t on purpose. I tried my best, but good questions are hard to write.

Question 1 will appear tomorrow.

Now that’s what I call a lag!

I received the following email the other day:

Dear Dr. Gelman,

I am emailing to let you know that your accepted article for Economic Inquiry will be published in print in the forthcoming April 2012 Issue. You will be receiving hard copies of the journal from Wiley-Blackwell for distribution to yourself and the Co Authors.

Hmmm . . . Economic Inquiry . . . didn’t I publish something there once? A quick check turned up this paper from 2010.

I wonder what this new paper is. Did someone submit something with my name on it? I remember my surprise when, many years ago, I received a postcard asking for a reprint of my article in the Journal of Cerebral Blood Flow and Metabolism. I was sure they were looking for the wrong Andrew Gelman, but, no, it turned out that my coauthors had submitted that article all on their own.

In this case, though, there was no new article. Economic Inquiry was indeed talking about my 2010 paper, which appeared online two years ago but is coming out in print only this month.

P.S. To add insult to injury: I wrote this post in March but it’s not appearing until May because I have a long lead time for non-topical entries on this blog.

Varying treatment effects, again

This time from Bernard Fraga and Eitan Hersh. Once you think about it, it’s hard to imagine any nonzero treatment effects that don’t vary. I’m glad to see this area of research becoming more prominent. (Here‘s a discussion of another political science example, also of voter turnout, from a few years ago, from Avi Feller and Chris Holmes.)

Some of my fragmentary work on varying treatment effects is here (Treatment Effects in Before-After Data) and here (Estimating Incumbency Advantage and Its Variation, as an Example of a Before–After Study).

The first version of my “inference from iterative simulation using parallel sequences” paper!

From August 1990. It was in the form of a note sent to all the people in the statistics group of Bell Labs, where I’d worked that summer.

To all:

Here’s the abstract of the work I’ve done this summer. It’s stored in the file,
/fs5/gelman/abstract.bell, and copies of the Figures 1-3 are on Trevor’s desk.
Any comments are of course appreciated; I’m at gelman@stat.berkeley.edu.

On the Routine Use of Markov Chains for Simulation

Andrew Gelman and Donald Rubin, 6 August 1990

corrected version: 8 August 1990

Continue reading ‘The first version of my “inference from iterative simulation using parallel sequences” paper!’ »

chartsnthings !

Yair pointed me to this awesome blog of how the NYT people make their graphs. This blows away all other stat graphics blogs (including this one). Lots of examples from mockup to first tries to final version. I recognize a lot of what they’re doing from my own experience. Also from my experience it’s hard to get all these details down: once you have the final graph, it’s easy to forget how you go there.

Happy news on happiness; what can we believe?

Sharon Jayson writes:

The conventional wisdom that’s developed over the past few decades — based on early research — has said parents are less happy, more depressed and have less-satisfying marriages than their childless counterparts.

But now, two new studies presented as part of the Population Association of America’s annual meeting suggest that earlier findings in several studies weren’t so clear-cut and may, in fact, be flawed. The newer analyses presented this week use analytical methods based on data from almost 130,000 adults around the globe — including more than 52,000 parents — and the conclusions aren’t so grim. They say that parents today may indeed be happier than non-parents and that parental happiness levels — while they do drop — don’t dip below the levels they were before having children. . . .

The other study, of some 120,000 adults from two nationally representative surveys between 1972-2008, finds that parents were indeed less happy than non-parents in the decade 1985-95, but parents from 1995 to 2008 were happier. . . .

This is consistent with my observation that happiness research is a mess. Don’t get me wrong: I think happiness is very much worth studying. But various seemingly well-known results don’t seem so clear when they are studied more carefully. This is not the first time that Happiness Scholar #2 comes to an opposite conclusion as Happiness Scholar #1.

The larger point, perhaps, is that it that “stylized facts” (the social-science term for generally-accepted findings) can mislead. Sometimes the interaction is bigger than the main effect.

Here’s a recent paper by Mikko Myrskylä, one of the researchers mentioned in the above article:

The literature on fertility and happiness has neglected comparative analysis. We investigate the fertility/happiness association using data from the World Values Surveys for 86 countries. We find that globally, happiness decreases with the number of children. This association, however, is strongly modified by individual and contextual factors. Most importantly, we find that the association between happiness and fertility evolves from negative to neutral to positive above age 40, and is strongest among those who are likely to benefit most from upward intergenerational transfers. In addition, analyses by welfare regime show that the negative fertility/ happiness association for younger adults is weakest in countries with high public support for families, and the positive association above age 40 is strongest in countries where old-age support depends mostly on the family.

The news article ends with the following comment:

“The first child increases happiness quite a lot. The second child a little. The third not at all,” says Myrskylä.

As a statistician, I hate hate hate hate hate when people ignore variability and present results deterministically. The above statement might be an accurate summary of average patterns but is certainly not true in every case!

The hare, the pineapple, and Ed Wegman

Commenters here are occasionally bothered that I spend so much time attacking frauds and plagiarists. See, for example, here and here. Why go on and on about these losers, given that there are more important problems in the world such as war, pestilence, hunger, and graphs where the y-axis doesn’t go all the way down to zero?

Part of the story is that I do research for a living so I resent people who devalue research through misattribution or fraud, in the same way that rich people don’t like counterfeiters.

What really bugs me, though, is when cheaters get caught and still don’t admit it. People like Hauser, Wegman, Fischer, and Weick get under my skin because they have the chutzpah to just deny deny deny. The grainy time-stamped videotape with their hand in the cookie jar is right there, and they’ll still talk around the problem. Makes me want to scream.

This happens all the time. All. Over. The. Place.

Everybody makes mistakes, and just about everybody does things they shouldn’t, every now and then. But to not apologize when you’re caught, that to me just seems evil, showing a disrespect not just for the people involved but for the very concept of truth. (As you can see, I wouldn’t make a good criminal defense lawyer.)

Anyway, here’s the latest story. There’s always an outrage-of-the-week, and I don’t mean to make a big deal about this particular scandal. It’s just another example of what I consider the disgraceful pattern of people refusing to admit error.

Part 1: The mistake
Continue reading ‘The hare, the pineapple, and Ed Wegman’ »

Lists of Note and Letters of Note

These (from Shaun Usher) are surprisingly good, especially since he appears to come up with new lists and letters pretty regularly. I suppose a lot of them get sent in from readers, but still.

Here’s my favorite recent item, a letter sent to the Seattle Bureau of Prohibition in 1931:

Dear Sir:

My husband is in the habit of buying a quart of wiskey every other day from a Chinese bootlegger named Chin Waugh living at 317-16th near Alder street.

We need this money for household expenses. Will you please have his place raided? He keeps a supply planted in the garden and a smaller quantity under the back steps for quick delivery. If you make the raid at 9:30 any morning you will be sure to get the goods and Chin also as he leaves the house at 10 o’clock and may clean up before he goes.

Thanking you in advance,

I remain
yours truly,

Mrs. Hillyer

Picking on Stephen Wolfram

Shalizi.

But this one is still my favorite.

Fun with google autocomplete

Aleks points us to this idea of labeling for news.

I’m skeptical about this skeptical article about left-handedness

I was flipping through the paper and noticed an opinion piece by linguist and science writer Rik Smits, “Lefties aren’t special after all”:

Few truly insignificant traits receive as much attention as left-handedness. In just the last couple of generations, an orientation once associated with menace has become associated with leadership, creativity, even athletic prowess. Presidents Gerald R. Ford, George Bush, Bill Clinton and Barack Obama were born left-handed (as was Ronald Reagan, though he learned to write with his right hand). Folklore has it that southpaws are unusually common in art and architecture schools. Left-handed athletes like Tim Tebow and Randy Johnson are celebrated.

Sounds interesting so far. Then we get several paragraphs of history of how people got things wrong (authoritarians of past generations who forced lefties to use their right hands, silly “blank slate” ideologues, etc.).

What about the science? Smits writes:

Left-handers have been redefined as creative, broad-minded, natural leaders. Meanwhile, other studies continue to identify all sorts of negative associations with left-handers — clumsiness, propensity to die prematurely, higher breast cancer rates and greater vulnerability to suicide.

After reviewing hundreds of such studies for a book on left-handers, I [Smits] found that the evidence of positive qualities associated with left-handedness was anecdotal at best, while the scores of studies associating left-handedness with all manner of afflictions were generally too unreliable to have any practical consequence.

I’d have to see Smits’s book to judge (and, before you get on my case for commenting on a book that I haven’t read, please reflect that Smits chose to publish his article in the Times, and I think it’s expected that many people will write a newspaper article without reading the corresponding book. Certainly, when I wrote op-eds about Red State Blue State, I wanted these to stand on their own for the benefit of the vast majority of newspaper readers who were not reading the book), but I’m skeptical of his skepticism. The studies I’ve seen of handedness do have potential problems, so I wouldn’t object to labeling as “speculative” such claims such as “mathematicians are more likely to be left-handed” or “left-handers live shorter lives than right-handers.” At the same time, such claims are not scientifically implausible, and they do seem supported to some extent by the data.

I have not looked at the research on handedness recently, so I’m not sure whether Smits’s skepticism reflects new information or whether it is just a statement that the claimed findings about left-handers have not been proved. If the latter, I think it would be better to say that it’s not clear to what extent left-handers are different from the majority, rather than to say with such certainty that “lefties aren’t special at all.”

P.S. I’m right-handed. I don’t have any personal stake in all this; it’s a topic I got interested in awhile ago when Seth and I taught our class on left-handedness. At the time we recognized the weakness of the studies on the topic, but we also recognized weaknesses in sweeping arguments that attempted to dismiss the findings by arguing for selection effects etc. My impression at the time was that there was some evidence of interesting and important systematic differences between lefties and righties, but that it was also possible we were seeing nothing more than a bunch of statistical artifacts. My conclusion was that skepticism was warranted but it would be going too far to be certain that nothing was going on.

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