Tuesday, January 19, 2016


The Power of the “Power Pose”

  and    from Slate

Amy Cuddy’s famous finding is the latest example of scientific overreach.

A Comic Con attendee poses as Wonder Woman during the 2014 New York Comic Con at Jacob Javitz Center on Oct. 9, 2014 in New York City.
Photo by Daniel Zuchnik/Getty Images

As practicing statisticians who work in social science, we have a dark secret to reveal: Some of the most glamorous, popular claims in the field are nothing but tabloid fodder. The weakest work with the boldest claims often attracts the most publicity, helped by promotion from newspapers, television, websites, and best-selling books. And members of the educated public typically only get one side of the story.
Consider the case of Amy Cuddy. The Harvard Business School social psychologist is famous for a TED talk, which is among the most popular of all time, and now a book promoting the idea that “a person can, by assuming two simple one-minute poses, embody power and instantly become more powerful.” The so-called “power pose” is characterized by “open, expansive postures”—Slate’s Katy Waldman described it as akin to “a cobra rearing and spreading its hood to the sun, or Wonder Woman with her legs apart and her hands on her hips.” In a published paper from 2010, Cuddy and her collaborators Dana Carney and Andy Yap report that such posing can change your life and your hormone levels. They report that the “results of this study confirmed our prediction that posing in high-power nonverbal displays (as opposed to low-power nonverbal displays) would cause neuroendocrine and behavioral changes for both male and female participants: High-power posers experienced elevations in testosterone, decreases in cortisol, and increased feelings of power and tolerance for risk; low-power posers exhibited the opposite pattern.”
Cuddy’s work on power posing has been covered in the press for years, including in Waldman’s tongue-in-cheek article in Slate. Most of the time, that coverage is glowing. Here’s a recent New York Times review of Cuddy’s new bookPresence: Bringing Your Boldest Self to Your Biggest Challenges: “While Cuddy’s research seems to back up her claims about the effects of power posing, even more convincing are the personal stories sent to the author by some of the 28 million people who have viewed her TED talk. … Unlike so many similar books aimed at ushering us to our best lives, Presence feels at once concrete and inspiring, simple but ambitious—above all, truly powerful.” And here’s a CBS News report from last month: “Believe it or not, her studies show that if you stand like a superhero privately before going into a stressful situation, there will actually be hormonal changes in your body chemistry that cause you to be more confident and in-command. … [M]ake no mistake, Cuddy’s work is grounded in science.”
But the story of power posing is not so simple. An outside team led by Eva Ranehill attempted to replicate the original Carney, Cuddy, and Yap study using a sample population five times larger than the original group. In a paper published in 2015,the Ranehill team reported that they found no effect.
This is not such a surprise. Cuddy’s scientific claim was, as is typically the case, based on finding “statistically significant” results in experiments. We know, though, that it is easy for researchers to find statistically significant comparisons even in a single, small, noisy study. Through the mechanism called p-hacking or the garden of forking paths, any specific reported claim typically represents only one of many analyses that could have been performed on a dataset. A replication is cleaner: When an outside team is focusing on a particular comparison known ahead of time, there is less wiggle room, and results can be more clearly interpreted at face value. The original power-pose study reported an impressively large effect, but that’s what happens with published results from small, noisy studies: Variation is high, so anything that does appear to be statistically significant (the usual requirement for publication) will necessarily be large, even if it represents nothing but chance fluctuation.
In a post from May 2015, psychology researchers Joe Simmons and Uri Simonsohnanalyzed the original power-pose study and its unsuccessful replication in detail, writing:
The power-posing participants were reported to have felt more powerful, sought more risk, had higher testosterone levels, and lower cortisol levels. In the replication, power posing affected self-reported power (the manipulation check), but did not impact behavior or hormonal levels. The key point of the TED Talk, that power poses “can significantly change the outcomes of your life,” was not supported.
Here’s their summary:

Courtesy of Joe Simmons and Uri Simonsohn
Simmons and Simonsohn write, “even if the effect existed, the replication suggests the original experiment could not have meaningfully studied it.” The replication showed similar negative results on hormones, and after an analysis of results from a collection of other published studies, they conclude, “at this point the evidence for the basic effect seems too fragile to search for moderators or to advocate for people to engage in power posing to better their lives.” In other words, the data are completely consistent with power poses having no effect. Or with a small undetectable positive effect. Or, for that matter, with a small negative effect.
Simmons and Simonsohn shared their analysis with Cuddy, who replied, “I’m pleased that people are interested in discussing the research on the effects of adopting expansive postures. I hope, as always, that this discussion will help to deepen our understanding of this and related phenomena, and clarify directions for future research. … I respectfully disagree with the interpretations and conclusions of Simonsohn et al., but I’m considering these issues very carefully and look forward to further progress on this important topic.”
Cuddy also pointed to a response that she had published, along with Carney and Yap, in the journal Psychological Science. Nowhere in that response, though, did Cuddy and her collaborators consider that their original paper may have been in error.
We understand this response—Cuddy has had a lot of success with this research so it would take a lot for her to give up on it—but we would prefer if she would consider the possibility that her original finding was spurious.
This is not to say that the power pose effect can’t be real. It could be real and it could go in either direction. We could imagine, for example, that sitting in a power pose gives people an overconfidence that could harm them in negotiations. Or that the power pose could help some people and hurt others. The point is, speculation is cheap. What got Cuddy and her theories such attention and respect, in addition to her excellent public-speaking skills, is the claim that it is “grounded in science”—the statistically significant result that was published in a top journal. But this evidence is thrown in doubt by the nonreplication of Ranehill et al., the careful analysis of other work by Simmons and Simonsohn, and the general statistical principles that explain how it is possible for researchers to find apparently strong evidence out of noise.
The unsuccessful replication got some scattered press coverage—the Huffington Post ran a story, for instance—but far less than the original claim received, and continues to receive, in the mass media.
If you read the New York Times, watch CBS News, or tune in to TED talks, you will encounter the power pose as solid science with a human touch. These media organizations portray it as a laboratory-tested idea that can help people live their lives better. But TV–approved and newspaper-endorsed social science is for outsiders. Insiders who are aware of the replication crisis in psychology research are suspicious of these sorts of dramatic claims based on small experiments. And you should be too.
The unsuccessful replication by Ranehill et al. appeared in mid-2015, as did the post by Simmons and Simonsohn. But half a year later, the Times and CBS continue to report Cuddy’s claims as fact. The CBS report includes only the most minimal sort of disclaimer:
There has been some criticism of Cuddy’s theories from other researchers, some saying that it only works in very specific kinds of circumstances.
“I welcome challenges that help us grow the science and move it forward,” said Cuddy. “The better we understand it, the better we can use it.”
This is completely misleading. The critics find no evidence that power posing “works” at all in the sense argued by Cuddy. As Simmons and Simonsohn write, “The key point of the TED Talk, that power poses ‘can significantly change the outcomes of your life,’ was not supported.”
Our point here is not to slam Cuddy and her collaborators Carney and Yap. We disagree with their interpretation of the statistics and are disappointed that they don’t seem to consider the possibility that their published result was spurious. But it is natural for researchers to feel strongly about their own research hypotheses. Outside research teams have attempted replications, these null results were themselves published, and science is proceeding as it should.

In writing this column, we hope to give you the perspective that you might not get from the
 New York Times, CBS News, or other news outlets that present gee-whiz science publications at face value. Rather, we want to highlight the yawning gap between the news media, science celebrities, and publicists on one side, and the general scientific community on the other. To one group, power posing is a scientifically established fact and an inspiring story to boot. To the other, it’s just one more amusing example of scientific overreach. So let’s put power posing where it belongs, alongside the claim that college men with fat arms are more likely to have certain political attitudes and that ovulating women are more likely to wear red.And we are not really criticizing the New York Times or CBS News, either. We all have been conditioned to believe that scientific publications represent truth, and it is taking the journalistic profession awhile to unlearn this lesson.

Sunday, January 10, 2016

Nutrition "science"

As the new year begins, millions of people are vowing to shape up their eating habits. This usually involves dividing foods into moralistic categories: good/bad, healthy/unhealthy, nutritious/indulgent, slimming/fattening — but which foods belong where depends on whom you ask.
The U.S. Dietary Guidelines Advisory Committee recently released its latest guidelines, which define a healthy diet as one that emphasizes vegetables, fruits, whole grains, low- or nonfat dairy products, seafood, legumes and nuts while reducing red and processed meat, refined grains, and sugary foods and beverages.1 Some cardiologists recommend a Mediterranean diet rich in olive oil, the American Diabetes Association gives the nod to bothlow-carbohydrate and low-fat diets, and the Physicians Committee for Responsible Medicine promotes a vegetarian diet. Ask a hard-bodied CrossFit aficionado, and she may champion a “Paleo” diet based on foods our Paleolithic ancestors (supposedly) ate. My colleague Walt Hickey swears by the keto diet.
Who’s right? It’s hard to say. When it comes to nutrition, everyone has an opinion. What no one has is an airtight case. The problem begins with a lack of consensus on what makes a diet healthy. Is the aim to make you slender? To build muscles? To keep your bones strong? Or to prevent heart attacks or cancer or keep dementia at bay? Whatever you’re worried about, there’s no shortage of diets or foods purported to help you. Linking dietary habits and individual foods to health factors is easy — ridiculously so — as you’ll soon see from the little experiment we conducted.
Our foray into nutrition science demonstrated that studies examining how foods influence health are inherently fraught. To show you why, we’re going to take you behind the scenes to see how these studies are done. The first thing you need to know is that nutrition researchers are studying an incredibly difficult problem, because, short of locking people in a room and carefully measuring out all their meals, it’s hard to know exactly what people eat. So nearly all nutrition studies rely on measures of food consumption that require people to remember and report what they ate. The most common of these are food diaries, recall surveys and the food frequency questionnaire, or FFQ.
Several versions of the FFQ exist, but they all use a similar technique: Ask people how often they eat particular foods and what serving size they usually consume. But it’s not always easy to remember everything you ate, even what you ate yesterday. People are prone to underreport what they consume, and they may not fess up to eating certain foods or may miscalculate their serving sizes.
“The bottom line here is that doing dietary assessment is difficult,” saidTorin Block, CEO of NutritionQuest, a company that conducts FFQs and was founded by his mother, Gladys Block, a pioneer in the field who began developing food frequency questionnaires at the National Cancer Institute. “You can’t get away from it — there’s error involved.” Still, there’s a pecking order in terms of completeness, he said. Food diaries rank high and so do 24-hour food recalls, in which an administrator sits the subject down for a guided interview to catalog everything eaten in the past 24 hours. But, Block said, “you really need to do multiple administrations to get an assessment of someone’s usual long-term dietary intake.” For study purposes, researchers are not usually interested just in what people ate yesterday or the day before, but in what they eat regularly. Studies that use 24-hour recalls tend to under- or overestimate nutrients people don’t eat every day, since they record only a small and perhaps unrepresentative snapshot.
When I tried keeping a seven-day food diary, I discovered how right Block was — it’s surprisingly difficult to capture a record that reflects normal eating patterns when you collect only a few days’ worth of data. It so happened that I was traveling to a conference during my diary week, so I ate packaged snacks and restaurant meals far different from the foods I usually eat from my garden at home. My diary showed that before dinner one day, I’d eaten only a doughnut and two snack packs of potato chips. And what did I have for dinner? I can tell you that it was a delicious Indonesian seafood curry, but I couldn’t possibly begin to list all its ingredients.
Pages from Christie's and Anna's food diaries.
Pages from the author’s and a colleague’s food diaries.
Another lesson from my short stint keeping a food diary is that the sheer act of keeping track can change what you eat. When I knew I had to write it down, I paid far greater attention to how much I ate, and that sometimes meant that I opted not to eat something because I felt too lazy to write it down or else realized, nah, I didn’t really want a second doughnut (or else didn’t want to admit to eating it).

It’s not easy to circumvent the human instinct to fib about what we eat, but the FFQ aims to overcome the unrepresentativeness of short-term food records by assessing what people consume over a longer period. When you read a headline saying something like “blueberries prevent memory loss,” the evidence usually comes from some version of the FFQ. The questionnaire typically asks about what the survey-taker ate during the last three, six or 12 months.
In order to get a sense of how these surveys work and how reliable they might be, we hired Block to administer his company’s six-month FFQ to me, my colleagues Anna Barry-Jester and Walt Hickey, and a group of reader volunteers.2
Some questions — how often do you drink coffee? — were straightforward. Others confounded us. Take tomatoes. How often do I eat those in a six-month period? In September, when my garden is overflowing with them, I eat cherry tomatoes like a child devours candy. I might also eat two or three big purple Cherokees drizzled with balsamic and olive oil per day. But I can go November until July without eating a single fresh tomato. So how do I answer the question?
Questions about serving sizes perplexed us all. In some cases, the survey provided weird but helpful guides — for example, it depicted what a half-cup, one cup or two cups of yogurt looked like with photographs of bowls filled with various amounts of wood chips. Other questions seemed absurd. “Who on this planet knows what a cup of salmon or two cups of ribs looks like?” Walt asked.
Although the questionnaire was meant simply to measure our food intake, at times it felt judgmental — did we take our milk full fat, low fat or fat free? I noticed that when I was offered three choices of serving sizes, my inclination was to pick the middle one, regardless of what my actual portion might be.
Despite these challenges, Anna, Walt and I did our best to answer completely and honestly. Afterward, we compared our results. The questionnaire deemed “cheese, full fat” and some version of alcohol as our top sources of calories.3
From there, our diets diverged. Walt has lost 50 pounds on a ketogenic diet, Anna eats relatively little protein and, according to the FFQ, I devour almost twice the calories as either of them.
Could these results be correct? Anna and I are virtually the same height and weight; we could probably share clothes. How could I eat more than twice the calories she does?4 Block acknowledged that it’s difficult to get an accurate count of calories, especially without a long-term food record, and when you start looking at individual nutrients it gets even trickier. He pointed me to a 1987 study concluding that to estimate a true average calorie count, it takes an average of 27 days of daily intake data for men and 35 days for women. Some nutrients required even longer — 474 days on average to measure vitamin A intake for women, for example. This suggests our reports might be correct, but they might also contain lots of errors.
Sure, memory-based measures have limitations, said Brenda Davy, a professor of human nutrition at Virginia Tech, “but most of us in the nutrition world still believe they have value.” Calories are probably the trickiest thing to measure, she said, noting that there’s good evidence thatpeople underreport foods deemed unhealthy, like high-fat foods or sugary snacks. “But that doesn’t mean that everything is underreported. It doesn’t mean that fiber intake or calcium intake is problematic.”
Developers of the surveys recognize that answers are imperfect, and they correct for this with validation studies that check FFQ results against those obtained via other methods, usually a 24-hour food recall or longer food diary. The results of such validation studies, Block said, allow researchers to account for variability in daily intake.
Critics of FFQs, such as Edward Archer, a computational physiologist at the University of Alabama’s Nutrition Obesity Research Center in Birmingham, say that these validations are nothing more than circular reasoning. “You’re taking one type of subjective report and validating it with another form of subjective report,” he said.
Recording what you eat is harder than it might seem, said Tamara Melton, a registered dietitian and spokesperson for the Academy of Nutrition and Dietetics in Atlanta. Among other things, it’s almost impossible to measure ingredients and portion sizes when you dine out. “It’s cumbersome. If you’re out at a business lunch, you can’t whip out your measuring cup.”
When Anna, Walt and I compared the caloric intakes that our FFQs had spit out with the ones that we calculated from our seven-day food diaries,5 they didn’t match up. We ran into trouble estimating portions in the FFQ, too, and who’s to say which was more accurate?
Although concerns about self-reported dietary intakes have been around for decades, the debate has come to a head in recent years, said David Allison, director of the University of Alabama’s Nutrition Obesity Research Center in Birmingham. Allison was an author of a 2014 expert report from the Energy Balance Measurement Working Group that called it “unacceptable” to use “decidedly inaccurate” methods of measurement to set health care policies, research and clinical practice. “In this case,” the researchers wrote, “the adage ‘something is better than nothing’ must be changed to ‘something is worse than nothing.’”

The problems with food questionnaires go even deeper. They aren’t just unreliable, they also produce huge data sets with many, many variables. The resulting cornucopia of possible variable combinations makes it easy to p-hack your way to sexy (and false) results, as we learned when we invited readers to take an FFQ and answer a few other questions about themselves. We ended up with 54 complete responses and then looked for associations — much as researchers look for links between foods and dreaded diseases. It was silly easy to find them.
Our shocking new study finds that …
Raw tomatoesJudaism<0.0001
Egg rollsDog ownership<0.0001
Energy drinksSmoking<0.0001
Potato chipsHigher score on SAT math vs. verbal0.0001
SodaWeird rash in the past year0.0002
LemonadeBelief that “Crash” deserved to win best picture0.0004
Fried/breaded fishDemocratic Party affiliation0.0007
BeerFrequent smoking0.0013
CoffeeCat ownership0.0016
Table saltPositive relationship with Internet service provider0.0014
Steak with fat trimmedLack of belief in a god0.0030
Iced teaBelief that “Crash” didn’t deserve to win best picture0.0043
BananasHigher score on SAT verbal vs. math0.0073
CabbageInnie bellybutton0.0097
The FFQ we used produced 1,066 variables, and the additional questions we asked sorted survey-takers according to 26 possible characteristics (left- or right-handed, for example). This vast data set allowed us to do 27,716 regressions in just a few hours. (You can see the full results on GitHub.) With that many possibilities to examine, we were guaranteed to find some “statistically significant” correlations that aren’t real, said Veronica Vieland, a statistician who directs the Battelle Center for Mathematical Medicine at Nationwide Children’s Hospital in Columbus, Ohio. Using a p-value of 0.05 or less as the metric for statistical significance (as is common) equates to an error rate of 5 percent, Vieland said. And with 27,716 regressions, that means we should expect about 1,386 false positives.6
But false positives aren’t the only issue. It was also very likely that we’d discover real correlations that are scientifically useless, Vieland said. For instance, our experiment found that people who trim the fat from their steaks were more likely to be atheists than those who ate the fat that god had provided for them. It’s possible that there’s a real correlation between cutting the fat from meat and being an atheist, Vieland said, but that doesn’t mean that it’s a causal one.
A preacher who advised parishioners to avoid trimming the fat from their meat, lest they lose their religion, might be ridiculed, yet nutrition epidemiologists often make recommendations based on similarly flimsy evidence. A few years back, Jorge Chavarro, a nutritional epidemiologist at the Harvard School of Public Health, advised that women trying to conceiveconsider swapping low-fat dairy foods for high-fat dairy products such as ice cream, based on FFQ data from an ongoing study of nurses. He and his colleague Walter Willett also wrote a book promoting a “fertility diet” based on the results. When I reached Chavarro this week to ask how confident he was in the link between dairy intake and fertility, he said that “of all the associations we found, this is the one we had the least confidence in.” It’s also, of course, the one that made headlines.

Nearly every nutrient you can think of has been linked to some health outcome in the peer-reviewed scientific literature using tools like the FFQ, said John Ioannidis, an expert on the reliability of research findings at the Meta-Research Innovation Center at Stanford. In a 2013 analysispublished in the American Journal of Clinical Nutrition, Ioannidis and a colleague selected 50 common ingredients at random from a cookbook and looked for studies evaluating each food’s association to cancer risk. It turned out that studies had found a link between 80 percent of the ingredients — including salt, eggs, butter, lemon, bread and carrots — and cancer. Some of those studies pointed to an increased risk of cancer, others suggested a decreased risk, but the size of the reported effects were “implausibly large,” Ioannidis said, while the evidence was weak.
But the problems weren’t just statistical. Many of the reported findings were also biologically improbable, Ioannidis said. For instance, a 2013 study found that people who ate three servings of nuts per week had a nearly 40 percent reduction in mortality risk. If nibbling nuts really cut the risk of dying by 40 percent, it would be revolutionary, but the figure is almost certainly an overstatement, Ioannidis told me. It’s also meaningless without context. Can a 90-year-old get the same benefits as a 60-year-old? How many days or years must you spend eating nuts for the benefits to kick in, and how long does the effect last? These are the questions that people really want answers to. But as our experiment demonstrated, it’s easy to use nutrition surveys to link foods to outcomes, yet it’s difficult to know what these connections mean.
FFQs “aren’t perfect,” said Harvard’s Chavarro, but at the moment there are few other options. “It may be that we have reached a limit of current methodology for nutritional assessments and it’s going to require a major shift to do something better,” he said.
Current studies suffer another fundamental problem: We expect far too much from them. We want to answer questions like, what’s healthier, butter or margarine? Can eating blueberries keep my mind sharp? Will bacon give me colon cancer? But observational studies using memory-based measures of dietary intake are tools too crude to provide answers with this level of granularity.
One reason is that single nutrients like saturated fat or an antioxidant seem to produce only trivial differences in the absolute risk of disease, Ioannidis said. (His conclusion comes from more rigorous randomized trials.) This is why headlines so often report relative risks — how many people got cancer in the group who ate the most bacon compared with those who ate none. Relative risks are almost always much more extreme than absolute risk, but absolute risk (your risk of getting cancer if you consume bacon, for instance) is what we really care about. If, say, 1 out of 10,000 people who ate the most bacon got cancer, compared with 3 out of 10,000 who ate none, that’s a threefold difference. But the difference in absolute risk — a 0.01 percent chance of cancer versus 0.03 percent — is tiny and probably not enough to change anyone’s eating habits.
The tendency to report results as more precise and important than they are also explains why we get so many back-and-forth headlines about things like coffee. “Big data sets just confer spurious precision status to noise,” Ioannidis wrote in his 2013 analysis.
So we’re left with our original question: What is a healthy diet? We know the basics — we need sufficient calories and protein to keep our bodies alive. We need nutrients like vitamin C and iron. Beyond that, we may be overthinking it, said Archer, the Nutrition Obesity Research Center physiologist. “We have cultures that eschew fruits and vegetables that were perfectly healthy for thousands of years,” he said. Some populations today thrive on very few vegetables, while others subsist almost entirely on plant foods. The takeaway, Archer said, is that our bodies are adaptable and pretty good at telling us what we need, if we can learn to listen.
Even so, I doubt we’ll give up looking for secret health elixirs in our pantries and refrigerators. There’s a reason the media and the public gobble up these studies, and it’s the same reason that researchers spend billions of dollars doing them. We live in a world where scary diseases constantly strike people around us, sometimes out of the blue. The natural reaction when someone has a heart attack or is diagnosed with cancer is to look for a way to protect yourself from a similar fate. So we turn to food to regain a modicum of control. We can’t direct what’s going on inside our cells, but we can control what we put into our bodies. Science has yet to find a magic vitamin or nutrient that will allow us to stay healthy forever, but we seem determined to keep trying.
CORRECTION (Jan. 6, 1:10 p.m.): A previous version of this article incorrectly described the affiliation of the Energy Balance Measurement Working Group, which wrote a report on obesity research methods. It is not affiliated with the National Cancer Institute, although there is another group with a similar name that is affiliated with the institute.

Christie Aschwanden reported and wrote this story and discovered two new foods — hush puppies and cheese straws (her new obsession) — in the process.Anna Maria Barry-Jester contributed reporting and photography. She also learned how hard it is to calculate the calories in gyro meat. Andrew Flowers p-hacked the hell out of our data, against his better judgment. For our survey,Walt Hickey identified important unanswered questions about the relationship between certain foods and bellybuttons, weird rashes and opinions of the movie “Crash.”


  1. The guidelines stirred immediate controversy. An editorial in the medical journal BMJ concluded that they lacked rigorous evidence, a claim that committee membersdisputed^
  2. Our “study” was just a rough experiment to explore how typical study methods work. We won’t be attempting to publish it in any scientific journal. ^
  3. Here are our top three sources of calories, as measured by the FFQ.
    • Christie: cheese (full fat), both red and white wine, oatmeal.
    • Anna: cheese (full fat), beer, mac & cheese/cheese dishes.
    • Walt: cheese (full fat), liquor/cocktails, peanuts, and other nuts and seeds.
  4. Sure, our levels of exercise may vary, and other things like body composition may factor in, but the level of disparity here shocked us both. ^
  5. Our calculations were akin to those you might get from a calorie-counting phone app. For packaged foods, we referenced the nutrition facts labels. For foods prepared at home or in restaurants, we referenced a variety of online sources, includingWolframAlpha and myfitnesspal, either for calories in similar recipes or the calories of individual ingredients. Studies involving food diaries typically follow a more rigorous process that includes detailed interviews to help participants remember and estimate what they ate and a more complicated nutrient analysis, often based on data from the U.S. Department of Agriculture National Nutrient Database for Standard Reference. Our numbers do not represent a comprehensive analysis of the calories we consumed. ^
  6. This error rate reflects only false positives due to sampling variability; it doesn’t say anything about other sources of error, such as inaccurate data. Statistician David Colquhoun has estimated that, in practice, a p-value of 0.05 yields at least a 30 percent error rate, and usually more. ^
Christie Aschwanden is FiveThirtyEight’s lead writer for science.