The widespread research declaring that women are happier single has long been retracted and refuted by experts as well as the original researcher.

https://www.vox.com/future-perfect/2019/6/4/18650969/married-women-miserable-fake-paul-dolan-happiness

How many times on feminist subs have you seen women parade the claim that a study proved that women are happier single? Even on this sub, whenever we so much as mention the "wall," many female PPD users will take that as their cue to make fun of PDD men for projecting their lonliness and failing to understand that women are independent now and won't give mediocre men chances anymore. Then they'll say something about how they saw their grandmothers suffer from low value men, "you aren't competing with other men, you're competing with the comfort women find in singlehood," and a hodgepodge of radfem verbatim.

But how reputable was this study they base their hubris on in the first place? Not very, as this article explains (I've highlighted the important bits).

Women should be wary of marriage — because while married women say they’re happy, they’re lying. According to behavioral scientist Paul Dolan*, promoting his recently released book Happy Every After, they’ll be much happier if they steer clear of marriage and children entirely.*

“Married people are happier than other population subgroups, but only when their spouse is in the room when they’re asked how happy they are. When the spouse is not present: f\**ing miserable,”* Dolan said, citing the American Time Use Survey, a national survey available from the Bureau of Labor Statistics and used for academic research on how Americans live their lives.

The problem? That finding is the result of a grievous misunderstanding on Dolan’s part of how the American Time Use Survey works. The people conducting the survey didn’t ask married people how happy they were, shoo their spouses out of the room, and then ask again. Dolan had misinterpreted one of the categories in the survey, “spouse absent,” which refers to married people whose partner is no longer living in their household, as meaning the spouse stepped out of the room.

Oops.

The error was caught by Gray Kimbrough, an economist at American University’s School of Public Affairs, who uses the survey data — and realized that Dolan must have gotten it wrong. “I’ve done a lot with time-use data,” Kimbrough told me. “It’s a phone survey.” The survey didn’t even ask if a respondent’s spouse was in the room.

Dolan confirmed to me by email, “We did indeed misinterpret the variable. Some surveys do code whether people are present for the interview but in this instance it refers to present in the household. I have contacted the Guardian who have amended the piece and my editor so that we can make the requisite changes to the book. The substance of my argument that marriage is generally better for men than for women remains.”

Kimbrough disputes that, too, arguing that Dolan’s other claims also “fall apart with a cursory look at the evidence,” as he told me.

This is only the most recent example of a visible trend — books by prestigious and well-regarded researchers go to print with glaring errors, which are only discovered when an expert in the field, or someone on Twitter, gets a glance at them. People trust books. When they read books by experts, they often assume that they’re as serious, and as carefully verified, as scientific papers — or at least that there’s some vetting in place. But often, that faith is misplaced. There are no good mechanisms to make sure books are accurate, and that’s a problem.

There are a few major lessons here. The first is that books are not subject to peer review, and in the typical case not even subject to fact-checking by the publishers — often they put responsibility for fact-checking on the authors, who may vary in how thoroughly they conduct such fact-checks and in whether they have the expertise to notice errors in interpreting studies, like Wolf’s or Dolan’s.

The second, Kimbrough told me, is that in many respects we got lucky in the Dolan case. Dolan was using publicly available data, which meant that when Kimbrough doubted his claims, he could look up the original data himself and check Dolan’s work. “It’s good this work was done using public data,” Kimbrough told me, “so I’m able to go pull the data and look into it and see, ‘Oh, this is clearly wrong.’”

Many researchers don’t do that. They instead cite their own data, and decline to release it so they don’t get scooped by other researchers. “With proprietary data sets that I couldn’t just go look at, I wouldn’t have been able to look and see that this was clearly wrong,” Kimbrough told me.