Bad Match? Dating, Living Together, and Divorce

The Jour­nal of Mar­riage and Fam­ily — pub­lished by the non-partisan, non-political National Coun­cil on Fam­ily Rela­tions — once released a report enti­tled “Pre­mar­i­tal Sex, Cohab­i­ta­tion, and Divorce: The Bro­ken Link” (PDF).

The pri­mary find­ings may deter­mine that pre­mar­i­tal sex and liv­ing together may cre­ate a bad match — dat­ing and mar­riage may be harmed by the behaviors:

• Pre­mar­i­tal sex and cohab­i­ta­tion with only the hus­band they end up mar­ry­ing does not increase the chance of divorce

• Mul­ti­ple premarital-sex part­ners among women increase the risk of divorce, regard­less of whether they lived with their part­ners (empha­sis added)

Although the report is from 2003, human nature does not change over cen­turies — let alone sev­en­teen years. And the results are now rush­ing through the blogosphere.

The Social Pathol­o­gist has taken the data in the full report (which seems to be avail­able only through pur­chas­ing the jour­nal) and cre­ated the chart seen at the top of this post. He sum­ma­rizes the report as such:

It is only women who have more than one inti­mate pre­mar­i­tal rela­tion­ship who have an ele­vated risk of mar­i­tal dis­rup­tion. This effect is strongest for women who have mul­ti­ple pre­mar­i­tal cores­i­den­tal unions.

Cit­i­zen Rene­gade, for­merly known as Roissy in D.C., is more — shall we say — blunt on the results of the find­ings:

Sluts may have higher testos­terone lev­els, lead­ing them to cheat and, thus, to increase mar­i­tal insta­bil­ity. Sluts may get bored faster with any one man. Sluts attract the sorts of men who them­selves have no use for monog­a­mous com­mit­ment. Sluts may just be fucked in the head. Their psy­chol­ogy doesn’t mat­ter as much as the abil­ity to quickly iden­tify and dis­card them as poten­tial wife and mother of your chil­dren material.

Vox Day chimes in:

While numer­ous female writ­ers advo­cate eva­sion, if not out­right decep­tion, it would appear that men would do well to make sure they have an accu­rate numer­i­cal his­tory in order to deter­mine which cat­e­gory a woman to whom they are attracted hap­pens to fall, high divorce risk or low divorce risk. There’s noth­ing wrong with pur­su­ing the for­mer, just don’t be sur­prised with the results when not only the odds, but the sta­tis­ti­cal evi­dence is stacked against you.

Of course, there is the valid sta­tis­ti­cal reply: cor­re­la­tion does not equal cau­sa­tion. There is an infa­mous Inter­net meme that takes this to heart. Take the alleged num­ber of pirates world­wide com­pared to aver­age global-temperature:

Unless pirates have access to some heretofore-unseen planet-warming tech­nol­ogy, it would be ludi­crous to state that the sea-faring scav­engers are con­tribut­ing to any cli­mate change. After all, the best way to judge whether one vari­able is affect­ing an out­come is to elim­i­nate all other vari­ables. (This is one rea­son why the the­ory that sex­ism is the cause of the gender-wage dis­par­ity is largely bunk.)

But there are two rebut­tals. First, two behav­iors that are closely related — dat­ing and divorce, unlike pirates and planet tem­per­a­ture — are much more likely to influ­ence each other. Sec­ond, there is still a way to deter­mine whether a vari­able affects an out­come if other vari­ables are unable to be elim­i­nated. The more that the rates of change between two graphs cor­re­late to each other, the more that cau­sa­tion is likely. I am not a sta­tis­ti­cal ana­lyst, so I invite any math­e­mati­cians to look at the data in the study and post the results in the comments.

Arti­cle Pages: 1 2