Making causal claims with correlative data

Via Steve Greene, here's an excellent Will Saletan piece interpreting the new National Survey of Sexual Health and Behavior.  (Seriously, why can't Saletan's articles all be this good?)  Saletan is trying to explain the somewhat counter-intuitive finding that anal sex seems to more reliably produce female orgasms than either vaginal or oral sex.  His explanation:

Only 6 percent of women who had anal sex in their last encounter did so in isolation. Eighty-six percent also had vaginal sex. Seventy-two percent also received oral sex. Thirty-one percent also had partnered masturbation. And the more sex acts a woman engaged in during the encounter, the more likely she was to report orgasm. These other activities are what gave the women their orgasms. The anal sex just came along for the ride.

So why did the inclusion of anal sex bump the orgasm figure up to 94 percent? It didn't. The causality runs the other way. Women who were getting what they wanted were more likely to indulge their partners' wishes. It wasn't the anal sex that caused the orgasms. It was the orgasms that caused the anal sex.

Loyal readers will recognize that I usually do not write about anal sex, except of course as a metaphor.  So why do I mention this here?  Because it's a great demonstration of how we make causal claims when all we have is a correlation.  A lot of social science data, particularly those derived from surveys, are just correlations.  There may be a causal relationship, but without some sort of experiment, it's usually difficult to be sure.  This is where theorizing plays a role.  We don't know for sure that Saletan's got the story right, but his explanation is plausible and empirically testable.