“You might think that’s OK”

If you’ve read my blog for a while, you’ve probably noticed that I treat US Republican politicians as if they were a hive mind. That’s obviously false, but when they act as a unit to continue family separation policies or put partisan hacks on the Supreme Court then their differences are small enough to safely ignore.

Today, we got another example of that. The Intelligence Committee within the US House of Representatives held a hearing on Russian interference. Rather than contribute towards that, however, every Republican on the committee used their time to demand the head of the committee step down. Why? According to a letter they released,

Despite these findings [of the Special Council report], you continue to proclaim in the media that there is “significant evidence of collusion.” You further have stated you “will continue to investigate the counterintelligence issues. That is, is the president or people around him compromised in any way to a hostile foreign power?” Your willingness to continue to promote a demonstrably false narrative is alarming.

Either Adam Schiff knew this was coming, or he’s damn quick on his feet, because he shot back with this. Forgive the length of this quote, but it’s worth absorbing in full. [Read more…]

Ugh, Not Again

P-values are back in the news. Nature published an article, signed by 800 scientists, calling for an end to the concept of “statistical significance.” It ruffled my feathers, even though I agreed with its central thesis.

The trouble is human and cognitive more than it is statistical: bucketing results into ‘statistically significant’ and ‘statistically non-significant’ makes people think that the items assigned in that way are categorically different. The same problems are likely to arise under any proposed statistical alternative that involves dichotomization, whether frequentist, Bayesian or otherwise.

Unfortunately, the false belief that crossing the threshold of statistical significance is enough to show that a result is ‘real’ has led scientists and journal editors to privilege such results, thereby distorting the literature. Statistically significant estimates are biased upwards in magnitude and potentially to a large degree, whereas statistically non-significant estimates are biased downwards in magnitude. Consequently, any discussion that focuses on estimates chosen for their significance will be biased. On top of this, the rigid focus on statistical significance encourages researchers to choose data and methods that yield statistical significance for some desired (or simply publishable) result, or that yield statistical non-significance for an undesired result, such as potential side effects of drugs — thereby invalidating conclusions.

Nothing wrong there. While I’ve mentioned some Bayesian buckets, I tucked away a one-sentence counter-argument in an aside over here. Any artificial significant/non-significant boundary is going to promote the distortions they mention here. What got me writing this post was their recommendations.

What will retiring statistical significance look like? We hope that methods sections and data tabulation will be more detailed and nuanced. Authors will emphasize their estimates and the uncertainty in them — for example, by explicitly discussing the lower and upper limits of their intervals. They will not rely on significance tests. When P values are reported, they will be given with sensible precision (for example, P = 0.021 or P = 0.13) — without adornments such as stars or letters to denote statistical significance and not as binary inequalities (P  < 0.05 or P > 0.05). Decisions to interpret or to publish results will not be based on statistical thresholds. People will spend less time with statistical software, and more time thinking.

This basically amounts to nothing. Journal editors still have to decide what to print, and if there is no strong alternative they’ll switch from an arbitrary cutoff of p < 0.05 to an ad-hoc arbitrary cutoff. In the meantime, they’re leaving flawed statistical procedures in place. P-values exaggerate the strength of the evidence, as I and others have argued. Confidence intervals are not an improvement, either. As I put it:

For one thing, if you’re a frequentist it’s a category error to state the odds of a hypothesis being true, or that some data makes a hypothesis more likely, or even that you’re testing the truth-hood of a hypothesis. […]

How does this intersect with confidence intervals? If it’s an invalid move to hypothesise[sic] “the population mean is Y,” it must also be invalid to say “there’s a 95% chance the population mean is between X and Z.” That’s attaching a probability to a hypothesis, and therefore a no-no! Instead, what a frequentist confidence interval is really telling you is “assuming this data is a representative sample, if I repeat my experimental procedure an infinite number of times then I’ll calculate a sample mean between X and Z 95% of the time.” A confidence interval says nothing about the test statistic, at least not directly.

In frequentism, the parameter is fixed and the data varies. It doesn’t make sense to consider other parameters, that’s a Bayesian move. And yet the authors propose exactly that!

We must learn to embrace uncertainty. One practical way to do so is to rename confidence intervals as ‘compatibility intervals’ and interpret them in a way that avoids overconfidence. Specifically, we recommend that authors describe the practical implications of all values inside the interval, especially the observed effect (or point estimate) and the limits. In doing so, they should remember that all the values between the interval’s limits are reasonably compatible with the data, given the statistical assumptions used to compute the interval. Therefore, singling out one particular value (such as the null value) in the interval as ‘shown’ makes no sense.

Much of what the authors proposed would be fixed by switching to Bayesian statistics. Their own suggestions invoke Bayesian ideas without realizing it. Yet they go out of their way to say nothing’s wrong with p-values or confidence intervals, despite evidence to the contrary. Their proposal is destined to fail, yet it got more support than the arguably-superior p < 0.005 proposal.

Maddening. Maybe it’s time I got out my poison pen and added my two cents to the scientific record.

Rapid Onset Gender Dysphoria

Remember that old thing? No? OK, quick summary:

Parental reports (on social media) of friend clusters exhibiting signs of gender dysphoria and increased exposure to social media/internet preceding a child’s announcement of a transgender identity raise the possibility of social and peer influences.

Littman L (2018) Parent reports of adolescents and young adults perceived to show signs of a rapid onset of gender dysphoria. PLoS ONE 13(8): e0202330.

In short, maybe social media is making the kids transgender? This seems like something someone should study, and someone did!

Poorly. [Read more…]

I Think I Get It

We seem to be in a cycle. Every time PZ Myers posts something about transgender people, the comment thread floods with transphobes. Given the names involved, I suspect this is due to Ophelia Benson’s effect on the atheio/skeptic sphere.

Regardless, there may be another pattern in play. The go-to argument of these transphobes was transgender athletes, with the old bathroom line showing up late in the thread. I had a boo at GenderCritical on Reddit, to assess if this was just a local thing, and noticed there were more stories about athletics than bathrooms over there. Even one of the bigots thought this was new. Has there been a shift of rhetoric among transphobes?

If so, I think I understand why.

[Read more…]

… and Ophelia Benson

That small thing? I saw a referer pop up from Butterflies and Wheels, when one of Ophelia Benson’s commenters linked to me as an example of outrageous behaviour. Whenever that happens, I refer back to the rule I established three years ago.

For my part, I wrote myself into a corner with that last post. “Ophelia Benson is transphobic” became a “dog bites man” story, there wasn’t anything new or notable about it. The best evidence was on the table, people had entrenched in their opinions, and there seemed little point in flogging that horse further. So I hate-read Benson for a few weeks or so, then got bored and stopped caring. Maybe twice in that time she’s been mentioned in my circles, I checked back in, asked myself and others “does this qualify as noteworthy?,” then after some deliberation decided it wasn’t.

This time, it was. So I did my homework, typed up the first of a two-part post, and promptly got distracted. I promised to return to it during Trans Awareness Week, then broke that promise as academics and life caught up to me. PZ’s post landed just as I was clawing back towards a more stable spot, so I dusted off those old drafts.

[Read more…]

A Year-End Wrap Up

… You know, I’ve never actually done one? They feel a bit self-indulgent, but having looked at the data I think there’s an interesting pattern here. Tell me if you can spot it, based on the eleven posts that earned the most traffic in 2018:

[Read more…]

And Then There Were Four

Now a fourth woman has told BuzzFeed News her experience of sexual harassment from Tyson. In January 2010, she recalled, she joined her then-boyfriend at a holiday party for employees of the American Museum of Natural History. Tyson, its most famous employee, drunkenly approached her, she said, making sexual jokes and propositioning her to join him alone in his office. In a 2014 email shared with BuzzFeed News, she described the incident to her own employer in order to shoot down a proposed collaboration with Tyson.

This shouldn’t be a surprise. Our culture does its best to silence the victims of sexual assault and harassment, while protecting those who engage in it, so victims rarely come forward. When someone is willing to stick their neck out, however, other victims realize the strength in numbers and join them with their own tales. Sometimes, this leads to a measure of justice; sometimes, not. Whatever the case, the culture of silence makes this avalanche look like a conspiracy or panic; how can so many people be victims, and why are they coming forward now?

For years, Amet had been trying to make the world listen to her account of a powerful man who had once assaulted her and derailed her life. Mainstream publications, including BuzzFeed News, were unable to adequately corroborate the events from so long ago, and did not publish her allegations. And internet commenters assailed her character and New Age lifestyle. Her claims may have stayed buried forever, if not for the women who saw in Amet’s story a shadow of their own.

“I saw that her credibility was being questioned in a way that honestly had a lot of racist and sexist and anti-religious undertones,” [another accuser] said. “I kinda figured if I had any credibility to lend to that so that she’s taken more seriously, I should do that.”

When you look at the science behind sexual assault and harassment, and rationally weigh it, neither question is a mystery. It is exactly what you’d predict would happen if “rape culture” existed.

And it suggests there may soon be five.