October 25, 2017

Not science yet

Three weeks ago there was a story in the Herald headlined Research reveals that divorce does run in the family (via Antonio Rinaldi on Twitter). The headline, as you’d expect, got the news wrong: the first sentence of the story is

Numerous studies have shown that children of divorced parents are more likely to get divorced when compared to those who grew up with parents who remained married.

The new claim was that divorce ‘runs in the family’ for genetic reasons. The researchers say

“Nearly all the prior literature emphasised that divorce was transmitted across generations psychologically.

“Our results contradict that, suggesting that genetic factors are more important.”

Now, when someone comes up with a finding that contradicts previous research and that they claim even they were surprised by, I’d want pretty good evidence. I’d want to look at what they actually found, and to see some discussion of how much the evidence is specific to adoptive families in a fairly homogeneous society such as Sweden.  In a perfect world, I’d want the story to have some independent input from someone who knows what ‘heritability’ means.  And I’d still worry about publication bias — maybe the academic journal would have published a paper saying ‘no, it’s still just environment’, but I bet the Herald wouldn’t have a story.

How good is the evidence in the story? Well, it has a link to the Daily Mail.

It’s pretty common for British science linkbait that turns up in the NZ papers to just link to the UK media. But here the research paper doesn’t even exist yet. The story says “will be published in an upcoming issue Journal Psychological Science.” Three weeks later, it’s still upcoming — this isn’t the usual problem of the embargo ending the day before a paper actually appears.

I can’t find a preprint or any other source of details, and as far as I can tell, the primary source for this story is a press release from Virginia Commonwealth University.

This isn’t science news.  It’s academic marketing.

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Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »