Margin of Σrror

Margin of Σrror -

“Trust, But Verify:” Quinnipiac and the GOP surge in the States

Recent weeks have seen a spate of good news for Republicans in Quinnipiac polls of several 2014 governor’s races. In Colorado, Democratic Governor John Hickenlooper leads conservative ex-Congressman Tom Tancredo (R-CO) by just one point, Republican Colorado Secretary of State Scott Gessler by only two points, and Republican State Senator Greg Brophy by just six points. In Connecticut, Democratic Governor Dan Malloy actually trails 2010 opponent and former U.S. Ambassador Tom Foley by three points. (Malloy also has single digits leads over other possible opponents with low name identification.)

In Ohio, Republican Governor John Kasich leads his likely Democratic opponent, Cuyahoga County Executive Ed FitzGerald, by fourteen percentage points. Finally, in what qualifies as good news for Republicans in Florida, unpopular Republican Governor Rick Scott trails now-Democratic former Governor Charlie Crist by ten points (previously, Scott had trailed by even larger margins).

So what is one to make of these polls? Are Republicans poised for a midterm rebound in these states or are these polls too rosy for Republicans?

First, it should be said that there is certainly a case to be made that the Democratic Party will fare at least somewhat poorly in the 2014 midterms. Traditionally, two-term presidents experience a six-year itch as their party loses offices around the county in their second midterm election (Bill Clinton in 1998 was an exception). Furthermore (and separate from the six-year itch), the Cook Political Report’s David Wasserman notes that Republicans have a built-in turnout advantage for the midterm elections. This built-in Republican edge in midterm turnout has grown especially large in recent years.

Second, at the same time, it is also unwise to uncritically accept the results of a single poll (or a series of polls from the same polling firm). As Nate Silver and Real Clear Politics have shown in recent elections, poll averages tend to perform well in forecasting election results (Silver weights polls based on the past quality of the polling firm, while Real Clear Politics uses an unweighted average). Indeed, it is not coincidental that the two Senate races that Silver’s model incorrectly predicted—North Dakota and Montana—suffered from a dearth of polling data.

This is not to say that Quinnipiac is necessarily any better or worse than any other polling firm. Indeed, a post-election analysis of polling accuracy from Nate Silver’s 538 blog rated Quinnipiac as 11th of the 23 polling firms that conducted at least 5 polls in the last three weeks of the campaign.

Yet, like every polling firm, Quinnipiac conducts a poll from time to time that seems to be an outlier. For example, a mid-September 2010 Quinnipiac Ohio poll showed John Kasich leading Ted Strickland by a whopping 17 points. According to Real Clear Politics, polls from several other polling firms who conducted polls at roughly the same time as Quinnipiac showed Kasich with a substantially smaller lead (Kasich ultimately won by 2 percent in November).

In keeping with what recent polls from Quinnipiac suggest, Republicans may well be surging in the states. But one should at least be somewhat skeptical of these results until they are confirmed by results from other polling firms (or even future polls from Quinnipiac in the same states).

A complete lack of skepticism, best epitomized by a recent piece from POLITCO declaring John Kasich as a model for GOP success in swing states, results in too great a willingness to accept as fact the results of a single poll. At the same time, a complete dismissal of these Quinnipiac polls would be equally (or perhaps even more) silly.

So what is the right approach? Acceptance of results combined with a healthy dose of skepticism until confirmed by other polls. Or as our 40th President was famous for saying about U.S. relations with the Soviet Union, “trust, but verify.”

Flexing those Conservative Muscles, Pt. II

In Part I, we discussed popular media coverage of a forthcoming Psychological Science article. The work by Michael Bang Petersen and his colleagues claims to show an evolutionary link between physical strength and the intensity of political beliefs. In Part II, we’ll push that causal claim a bit further.

In the past few days, furor over the NSA surveillance program sparks new debates between liberals and conservatives. Interestingly, much the defense-versus-liberty arguments pit conservatives against one another: defense-hawks who want liberal power to root out terrorists, and libertarian-minded conservatives who abhor anything smelling like a police state.

This calls to mind the more traditional “liberals are like mothers, conservatives are like fathers” trope. Conservatives are tough and strong while liberals are warm and nurturing. The recent piece by Petersen and his colleagues plays, in part, into that stereotype. But how reliable is the research?

Revisiting Causation

Petersen and his colleagues find a correlation between bicep size (their measure of fighting aptitude) and the congruence between individual economic conditions and political conservatism. Why might the relationship exist? The authors argue that this clearly points to evolutionary and thus genetic bases of political attitudes. That’s not impossible, but it’s hardly the only reasonable conclusion to draw.[1]

Before we dig too deeply into the research, it might serve to review the basics of causal inference. Causation, as the name implies, seeks to establish that some phenomenon causes another. On its surface, this is simple to do. I flip the light switch, the light comes on. Boom: cause produces effect. Sure, there are mechanisms that allow the switch to work, but for all intents and purposes I caused the lights to come on.

Unfortunately, causal inference is rarely so simple. The cleanest way to observe causation is through randomized experiments, where some subjects receive a treatment (some rooms get the light switch flipped) and others don’t (some rooms’ switches are left untouched). If the treatment group experiences different outcomes than the control group, we may have observed a robust causal process.

With observational data (i.e., data collected by observation and not by experimentation), testing causal theories gets stickier. We can observe correlations, but we often cannot determine if x caused y, if y caused x, or if both x and y were caused by some other unobserved phenomenon z.

In political terms, we might ask: Does my evaluation of the economy determine my partisanship? Does my partisanship determine my evaluation of the economy? Does my political ideology cause both? Or might they all three interact in a more complicated way? With observational data, it’s hard to tell.

We don’t just abandon causal inference here, though. We can still make causal claims, but we must (a) provide thorough theoretical explanations for how our posited cause produces a certain effect; and (b) exhaustively examine alternate explanations that might falsify our theory.[2] Petersen and his colleagues tentatively satisfy the first condition, but hardly attempt at the latter.

Examining the Research

Turning back to the research, we can note first that the effects proffered by the authors are quite small. This illuminates the difference between statistical and substantive significance, which is frequently overlooked. The effect may exist, but it’s so small as to be swamped by other other influences in real world.

The more important challenge, however, critiques the authors’ causal claims. The authors posit that survival likelihood in men should cause more self-interested behavior, but they rather lazily support their case. In fact, the authors don’t even get close to providing an exhaustive test of their causal story.

The authors instead show a correlation between the two phenomena. Yet other reasonable explanations abound. Bicep size, after all, is not purely innate, but depends in large part on resistance training and even body fat percentage. And the predispositions toward having large arms may reflect little about evolution or genetics.

Certain people are more likely to believe strongly in physical aptitude and healthfulness, and perhaps these people are also more likely to hold strong political views. Education, for instance, tends to predict both political sophistication and physical exercise, health and lower obesity. Political science research also shows that knowledge and interest in politics play an important role in our ability to match economic policies and political elites to our personal economic well-being.

Or maybe the story does involve assertiveness, which makes individuals more likely to care about politics, behave more self-interestedly and/or hit the gym more regularly. The mechanism here could be nature, but it could also be nurture. Guys who are raised to assert their opinions on any manner of subjects, politics included, may also be raised to be physically strong.

Or perhaps self-interest causes physical fitness. It could be that people who are more self-interested also tend to care about physical strength. From a survival perspective, that would make sense. In fact, none of these alternative explanations are wholly unreasonable, and any of these explanations could produce similar correlations as expounded in the study.

Of Science and Old Sayings

The age-old bromide “correlation does not imply causation” should be ringing in our ears about now. The authors have a mildly interesting finding, but at root all they’ve presented is a correlation which hardly supports their causal story.

Image courtesy of

Unless future research shows that other fitness characteristics, condition political attitudes, the theory remains weak.

Even in that case, researchers need to rule out competing theories. Strength might cause self-interest; but self-interest could cause strength, or both could be the effects some another evolutionary or behavioral cause.

What To Do?

How might researchers better examine the connection between strength and political attitudes? Let’s consider a few things to try.

1. Measure strength, not (just) biceps: The authors argue that biceps are the best single predictor of fighting ability. But why use just one? Surely there are reasonable ways to measure strength, like with compression springs, that would give us a better idea of how strong participants are. This eliminates concerns that bicep size might be a poor indicator of strength.

2. Measure fighting ability, not just strength: Biceps (or strength, otherwise defined) only matters to the degree that it taps into fighting ability. Other characteristics help us fight, though. Height and longer arms are useful, as are stronger legs and faster reflexes. The authors argue that biceps are used by others to assess a person’s fighting ability, but that should not matter for this study. The theory suggests that good fighters, not people who just look like good fighters, should take what they want from the political system.

3. Explore innate characteristics: Behavior, personality and interpersonal influence (parents, peers, et cetera) affect our tendency to lift heavy things. That makes it nearly impossible to say that strength per se influences our political views. More innate qualities, not as subject to behavioral manipulation, could be helpful.

4. Consider other dimensions of assertiveness: The authors argue that strong men will be more politically assertive; but why stop there? Asking, or experimenting, with other facets of assertiveness may shed light on an interesting question, namely whether strength predicts certain personality types, politics included.


In sum, it’s not surprising that conservative outlets latched onto the research without reading it thoroughly. Conservatives on my Facebook feed were certainly thrilled to learn that they were, in fact, ruggedly strong and athletic, standing in stark contrast to their pantywaist liberal counterparts. That’s motivated reasoning at it’s best, but its also wrong.

And frankly, I’m not even too surprised that a peer-reviewed article would oversell its findings. The research garnered a lot of attention and, if true, could constitute a generally interesting finding.

But science isn’t about pithy titles or provocative theories. Causal claims must be made carefully, especially when working with observational data without randomization and controlled treatments. Time will expose the authors’ theory to better tests, and I suspect that when that happens, the theory will find its way to the scientific dustbin.



1. I’m fairly agnostic to using biological research in political science. Like all research subfields, it produces some good and some mediocre products. Some of the bio-politics research is actually interesting, some reflects a fetish for new data with little theoretical development, and some just mines for significance stars (see § 3).

2. This is actually a more optimistic view of causal inference in the social sciences than I tend to embrace. For an interesting read on causation writ large, I recommend Causality by Judea Pearl (see also here). For a grounded, if slightly depressing, view of statistical models and causal inference, David Freedman’s posthumous collection is a must read.

Flexing those Conservative Muscles, Pt. I

Several media outlets recently published an astonishing finding: strong men are more conservative. Based on an article in Psychological Science, the popular accounts stray far from the research and probably even further from the truth. In this two-part post, we’ll discuss what the researchers actually said (Pt. I) and what their research might actually mean (Pt. II).

Strong Men are Conservative!

Last week, my Facebook feed brought me some intriguing news: researchers apparently discovered that physically stronger men tend to hold conservative economic views.

A couple quick clicks and a Google search showed ample coverage, much in conservative media, of the peer-reviewed article. Michael Bang Petersen and his coauthors did, indeed, find a relationship between physical strength and political attitudes.

The study’s authors examine the connection between strength and politics by interviewing men and women in three countries (Argentina, Denmark and the United States). They measure the flexed, dominant-arm bicep of participants, and ask them a battery of political questions. The relationship is “statistically significant” at conventional levels.

So, are beefy men more conservative? Nope. Popular accounts of the research misinterpret the findings, which are themselves oversold by the authors. At no point do the data provide exhaustive support for the theory that physical strength causes any part of one’s political views, much less that it makes men more conservative.

Leveling the mountain to uncover the molehill

The study’s authors nest their theory in the evolutionary advantage strong men enjoy in physical conflicts. Members of the conservative press seemed to love this story, and thus extracted the evolutionary thread without reading beyond the article’s abstract.

The logic, according to the popular accounts, claims that since nature favors strong males, these same males will eschew social safety nets. They don’t need it, after all, and would rather not see the fruits of their strength redistributed to the ninnies.

Here’s the kicker: that’s not at all what the authors claimed to find. For the story above to be supported by data, we would expect bicep size to positively correlate with conservative views. It’s presumably not, given that they don’t publish that finding.

The authors posit instead that strength interacts with other characteristics to affect political views. They point out that traditional rational decision making models don’t perform so well in the electorate, especially when using economic wellbeing to predict attitudes. That is, rich people tend to support redistribution less than poorer people, but the relationship between wealth and economic attitudes isn’t as clean as we may expect.

Here enters strength: stronger males may be more willing to engage in self-interested behavior than their weaker counterparts. The authors explain that strong males would, in nature, be more likely to claim resources because they are more able to defend them, and the same may be true of political resources. Strong, rich men may be more willing to fight against redistribution, while stronger, poor men may be more willing to claim resources through redistribution.

That’s a horse of a different color. According to the authors’ account, strength does not predict conservatism, but instead predicts the congruence of personal economic status and political views. The authors do not present a correlation between strength and attitudes, but an interaction term between bicep size and wealth that together predict conservatism.[1]

How did it go so wrong?

I have several quibbles with the original research, which we’ll explore in Part II, but we should be clear: the authors did not claim to have found that strength relates to conservatism. That’s wholly an invention of either lazy or ulteriorly motivated journalists.

On one level, this shouldn’t be surprising. Of my friends who posted stories about the research, all are quite conservative. The story provides a feel-good boost to people who identify with conservative politics, and it’s not odd that they would share the good news.

Second, the original theory matches our collective political notions. Cowboys are conservative, academics are liberals; soldiers are conservative, environmentalists are liberals. Given this natural frame, it’s easy enough to package the findings in a way that calls to mind these biases. Of course strong men oppose redistribution! They’re rugged, self-sufficient, independent, and thus the perfect candidates for conservative political views. The more nuanced story, of strength conditioning self-interest, is more difficult to tell and less intuitive, so it gets left by the roadside.

Third, media face powerful incentives to hyperbolize. “Strong men are more conservative” is flashier and more provocative than “strong men more likely to act self-interested in economic policy preferences.” A story guaranteed to tickle conservatives and enrage liberals will also attract more shares, tweets, and trackbacks in the blogosphere. If there’s no such thing as bad publicity, perhaps there’s also no such thing as bad web traffic.

Surprising or not, the coverage should still be depressing and alarming. In an era where we’re debating the role of social science research in society, it’s important to understand how the public accesses major findings and how these may improve the democratic process. News media play an important role here, but that responsibility is corrupted when journalists choose sexy over scientific.

In Part II, we’ll discuss the research by Petersen and his colleagues, and explore the relationship between strength, economics and political attitudes.


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Americans Secretly Oppose Gay Marriage

If you’ve struggled to find humor in politics recently, rejoice. At least the skewed-polls people are still around.

Yesterday, Chris Stirewalt blogged for Fox News that polls overstate support for gay marriage. Voicing a similar belief, leading social conservative Gary Bauer showed little concern over public opinion, telling Fox’s Chris Wallace:

“No, I’m not worried about it because the polls are skewed, Chris. Just this past November, four states, very liberal states, voted on this issue. And my side lost all four of those votes. But my side had 45, 46 percent of the vote in all four of those liberal states.”

As with many fallacies, there’s an iota of truth here. Stirewalt draws on work by New York University political scientist Patrick Egan that shows that late-season polls typically overestimate support for gay marriage compared with the election returns.

I don’t really have a problem so far. A Pollster article by Harry back in 2009 made a similar point and explored some ways to improve predictive models. The gap between pre-election polls and election returns, in other words, is well documented.

So, the polls are skewed…

Here’s where I depart from most interpretations of this observation. The poll-vote gap does not necessarily imply that the polls are “skewed.” Could it? Yes. But it doesn’t need to. I suspect a good bit of the bias comes from who votes not how they vote.

Stirewalt argues that the polls are skewed and mainly blames social desirability bias. In this line of reasoning,  respondents do not want to admit opposition to gay rights for fear of social judgement; instead, they act supportive but cast their secret ballot against. In other words, the “true” level of support is systematically lower than the polls show.

What’s crazy to me is that Stirewalt, even after basing his entire argument on Egan’s research, ignores the part where Egan dismisses social desirability as the primary cause of the polls’ inaccuracy. And Egan couldn’t be much plainer about it: “On the whole, these analyses fail to pin the blame for the inaccuracy of polling on same‐sex marriage bans on social desirability bias” (p. 7)1.

What seems most likely is that pollsters haven’t figured out how to calibrate their samples to match the turnout. Ballot measures only attract at least moderately engaged observers. On an issue like gay marriage, it’s not surprising that some who ostensibly support gay rights aren’t nearly as motivated as those who have social, cultural or religious objections to it. The polls may decently represent the “true” proportion of citizens who support gay marriage, but not the class of voters who cast a ballot on the issue.

We’re Missing the Point

But far, far more importantly, any potential skew in the polls misses the true point here. Let’s assume that the polls are skewed, and that “true” support for gay marriage is actually seven points (best guess from the Egan research) lower than the polls say.

So what?

Those who invoke public opinion aren’t really that worried about crossing 50 percent. Even if the polls exaggerate support for gay marriage, the trend favors the equal rights argument. The above figure2 shows general sentiment (“thermometer” scores) toward gays and lesbians in the American National Election Study3This figure by Nate Silver shows a similar rise in support for gay marriage. And this figure from Gallup shows a widening gap favoring general rights for gays and lesbians.

In this light, even yelling “Skewed Polling!” doesn’t change the fact that support for gays and their ability to marry is rising steadily.
Now I know that race and sexual orientation are not the same, but there are some similarities between the above kernel density plot and the one at the top of the post. In general, support for rights and general sentiment co-evolve. Sentiment toward black Americans has increased even in the post-Civil Rights era. We see a smaller but similar “swell” in sentiment for homosexuals, with every reason to think it will continue on its current trajectory.

Even if support today is really say, 51 percent instead of 58 percent, it’s much higher than it used to be.

Could we just be getting more politically correct, instead of more ‘liberal’, on gay rights? Sure, but the green line in the time series doesn’t show any real change in the rate of respondents opting out. No, young people are coming of age with a more permissive view on this issue.

Skew or no, the trend speaks for itself.

[1] Now, as a brief aside, Egan’s first test for social desirability bias makes no sense to me. I can imagine plenty of reasons why a state’s gay population wouldn’t predict the poll-election gap. But the second test is much stronger: despite the social acceptance of LGBTs growing, the gap has become smaller. All in all, I’m sure social desirability is part of the story, but it’s most likely not the primary factor.

[2] The figure shows thermometers scaled on the interval [0, 1], as well as the proportion of respondents who respond to gays warmly (therm > 0.5), cooly (therm < 0.5), and those who opt to not answer. Confidence bands are generated using 1,000 bootstraps from the survey margin of error. The margin around “skip” seems odd, but for convenience I’m treating “skip” as an expression of a desire to not answer, and thus as a random variable in its own right.

[3] The ANES, funded by the National Science Foundation, could be at risk thanks to recent Congressional targeting of political science. Contact your representatives in Congress because (I promise!) most scholars use the study for more consequential research than I.