While commentators have been stumbling over themselves to determine what the study's findings mean about gender, marriage, and society, no one seems to be bothering to notice that the study itself appears pretty useless. The major conclusion, linking income and infidelity, has a number of problems, not the least of which is that everyone -- myself included -- who wasn't at the conference is relying on a press release and subsequent media reports about it. Such reports are notoriously unreliable, often drawing ideas from generous and/or speculative interpretations of the results rather than the study itself. That said, here are three of the reasons I'm particularly skeptical:
1. Do the math. The National Longitudinal Survey of Youth, upon which the study is based, followed about 9,000 individuals -- surely a healthy sample size. But the infidelity study examined only those who were married or with a live-in partner for more than a year, which is a much smaller subset. And of those, only seven percent of men and three percent of women actually fessed up to cheating during the study's six-year period. So, let's be generous and say that two-thirds of the NLSY group met the relationship-status criteria (n=6,000). And we'll presume that roughly half are of each gender (3,000 men and 3,000 women). That leaves us with about 210 men who have fessed up to infidelity in this survey. Of those, it is not clear from the media reports how many were in situations where the male earned less than his partner; other recent research suggests about a third, or fewer than 80 of those reporting infidelity, were in such a relationship. And remember, we're being generous because we do not have the actual numbers. To be sure, 210 male cheaters is still a decent sample, and it could be enough to draw meaningful conclusions about links between infidelity and income (among other factors). But it still is not a lot. In fact, it probably is a lot less than the number of participants in the survey who actually cheated. Remember...
Updated 2010-08-20: LiveScience.com (which has more details on the methodology, and as an added bonus, commentary from Stephanie Coontz) is reporting that only 3.8 percent of men, and 1.4 percent of women, admitted to cheating in the study. That's not exactly true; on average, 3.8 percent of men and 1.4 percent of women admitted to cheating in any given year of the six-year study, at least according to the press release.
2. People lie. A major income discrepancy in the relationship may be a good reason for men to simply be more honest about their cheating. Sure, you could argue, if the wife/girlfriend finds out then the gravy train ends. But if the man is in a relationship for the money, and not emotionally committed, why on earth would he lie to an anonymous survey about his cheating? There is little incentive to, and there is no cognitive dissonance to resolve over telling the truth. On the other hand, if he is emotionally engaged, and is in the relationship for reasons other than money, he may find it safer (and more palatable) to hide any previous infidelity. If all that sounds awfully speculative, well, that's the point. People lie on studies like this, and we do not always know who will be most likely to lie or why. Yet commenters (and, too often, the researchers themselves, as seems to be the case here) treat the findings as truth in spite of their huge flaws, and then seek to divine an explanation.
3. Account for other factors, like age, education, and religion, and the income-infidelity link vanishes. That inconvenient fact is actually in the press release, but of course, no one is paying attention to it. Does earning more than your man make him more likely to cheat? the chatterers are asking. In a word, no -- the income issue appears to (at best, and even this has big holes) correlate with, but not be a cause for, cheating.
The trouble with any study of undesirable behavior that relies on self-reports is that it is impossible to know what we're really studying -- the behavior itself, or the act of reporting it. Only a more carefully (and expensively) constructed study could parse that out. In the meantime, move on. Nothing new to see here.