Over the past few weeks, I’ve been thinking about consent. Feminists love to talk about it. And with good reason! It’s important, and it needs to be talked about. But at times, I have found the discussion rather narrow. Most often, consent is discussed in the context of sex. And there’s nothing wrong with that—certainly sex is a big area where consent matters. I don’t wish to downplay or belittle the important efforts made to talk about consent in the sexual realm. But to me, consent is much more than about sex—it reveals a meaningful way to think about how to treat people ethically. Consent really forms the backbone of my broader ethical framework, and I want to unpack that a bit.Continue Reading
Several years ago, Uri Simonsohn (along with Leif Nelson and Joe Simmons) introduced the psychology community to the idea of p-hacking, and his related concept for detecting p-hacking, the p-curve. He later demonstrated that this p-curve could be used as an estimate of true effect size in a way that was better at correcting for bias than the common trim-and-fill method.
Now, more recently, Ulrich Schimmack has been making a few waves himself, using his own metric called the R-index, which he has stated is useful as a test of how likely a result is to be replicable. He has also gained some attention for using it as what he refers to as a “doping test”, to identify areas of research—and researchers themselves—that are likely to have used questionable research practices (QRPs) that may have inflated the results. In his paper, he shows that his R-index indicates an increase in QRPs from research in 1960 to research in 2011. He also shows that this metric is able to predict the replicability of studies, by analyzing data from the Reproducibility Project and the Many Labs Project.Continue Reading
Back in May, Uri Simonsohn posted an article to his blog about studying effect sizes in the lab, with the general conclusion that the sample sizes needed for a precise enough estimate of effect size make it essentially not feasible for the majority of lab studies. Although I was not at the recent SESP conference, I have been told he discussed this (and more!) there. Felix Schönbrodt further discussed Simonsohn’s point, noting that reporting the effect size estimates and confidence intervals is still important even if they are wildly imprecise, because they can still be used in a meta-analysis to achieve more precision. I think both of these posts are insightful, and recommend that you read them both. However, both of them use particular examples with a given level of precision or sample size to illustrate their points. I wanted to go a bit more in-depth on how the precision level and effect size changes the sample size needed, using a tool in R that Schönbrodt pointed out.Continue Reading
I’ve been watching the recent debate about replication with interest, concern, and not just a little amusement. It seems everyone has their opinion on the matter (leave it to a field of scientists to have twice as many opinions as there are scientists in the field!), and at times the discussion has been quite heated. But as a grad student, it’s been difficult to know whether I should throw my own hat in the ring. With psychology heavyweights like Kahneman and Gilbert voicing their opinions, what room is there for a third-year grad student? But fortunately (or unfortunately), I’ve never been one to know when to keep my opinions to myself, so I want to present my own thoughts on the matter. My perspective is that, even if the issue gets heated at times, this discussion can be fruitful as we learn to navigate a changing discipline.Continue Reading