flynn002

-->   This blogpost doesn't say anything new – it just uses a new analogy (at least new to me) to make a point about the value of null results from well-designed studies. I was thinking about this after reading this blogpost by Anne Scheel. Think of science like prospecting for kryptonite in an enormous desert. There's a huge amount of territory out there, and very little kryptonite. Suppose also that the fate of the human race depends crucially on finding kryptonite deposits. Most prospectors don't find kryptonite. Not finding kryptonite is disappointing: it feels like a lot of time and energy has been wasted, and the prospector leaves empty-handed. But the failure is nonetheless useful. It means that new prospectors won't waste their time looking for kryptonite in places where it doesn't exist.  If, however, someone finds kryptonite, everyone gets very excited and there is a stampede to rush to the spot where it was discovered. Contemporary science works a bit ...

The tl;dr version A neuroimaging measure is potentially useful for individual differences research if variation between people is substantially greater than variation within the same person tested on different occasions. This means that we need to know about the reliability of our measures, before launching into studies of individual differences. High reliability is not sufficient to ensure a good measure, but it is necessary . Individual differences research Psychologists have used behavioural measures to study individual differences - in cognition and personality - for many years. The goal is complementary to psychological research that looks for universal principles that guide human behaviour: e.g. factors affecting learning or emotional reactions. Individual differences research also often focuses on underlying causes, looking for associations with genetic, experiential and/or neurobiological differences that could lead to individual differences. Some basic psychometrics Suppose...

This post was prompted by an interesting exchange on Twitter with Brent Roberts (@BrentWRoberts) yesterday. Brent had recently posted a piece about the difficulty of bringing about change to improve reproducibility in psychology, and this had led to some discussion about what could be done to move things forward. Matt Motyl (@mattmotyl) tweeted: I had one colleague tell me that sharing data/scripts is "too high a bar" and that I am wrong for insisting all students who work w me do it And Brent agreed: We were recently told that teaching our students to pre-register, do power analysis, and replicate was "undermining" careers. Now, as a co-author of a manifesto for reproducible science , this kind of thing makes me pretty cross, and so I weighed in, demanding to know who was issuing such rubbish advice. Brent patiently explained that most of his colleagues take this view and are skeptics, agnostics or just naïve about the need to tackle reproducibility. I said that w...

I'll shortly be posting a preprint about methodological quality of studies in the field of neurogenetics. It's something I've been working on with a group of colleagues for a while, and we are aiming to make recommendations to improve the field. I won't go into details here, as you will be able to read the preprint fairly soon. Instead, what I want to do here is to expand on a small point that cropped up as I looked at this literature, and which I think is underappreciated. It's to do with sampling. There's a particular problem that I started to think about a while back when I heard someone give a talk about a candidate gene study. I can't remember who it was or even what the candidate gene was, but basically they took a bunch of students, genotyped them, and then looked for associations between their genotypes and measures of memory. They were excited because they found some significant results. But I was, as usual, sitting there thinking convoluted though...

Image from: https://fdudhwala.wordpress.com/2017/01/05/first-time-publishing-woerries/ I posted a couple of tweets yesterday giving my personal view of things to avoid when writing a job application. These generated a livelier debate than I had anticipated, and made me think further about the issues I'd raised. I've previously blogged about getting a job as a research assistant in psychology; this piece is directed more at early career researchers aiming for a postdoc or first lectureship. I'll do a separate post about issues raised by my second tweet – inclusion of more personal information in your application. Here I'll focus on this one:   Protip for job applicants: 3+ 1st author 'in prep' papers suggests you can't finish things AND that you'll be distracted if appointed I've been shortlisting for years, and there has been a noticeable trend for publication lists to expand to include papers that are 'in preparation' as well as those that...

--> I am beginning to develop an addiction to Hansard, the public record of debates in Parliament and the House of Lords. It's a fascinating public record of how major political decisions are debated, and I feel fortunate to live in a country where it is readily available on the internet the day after a debate. The debate on Donald Trump's state visit was particularly interesting, because it was prompted by a public petition signed by 1.85 million people, which read: Donald Trump should be allowed to enter the UK in his capacity as head of the US Government, but he should not be invited to make an official State Visit because it would cause embarrassment to Her Majesty the Queen. I've been taking a look at the debate from 20 th February, which divided neatly down party lines, with the Conservatives and a single DUP member supporting the state visit, and everyone else (Labour, Lib Dems, SNP and Green) opposing it. A notable point about the defenders of the State Visit i...

After watching this interview between BBC Newsnight's Evan Davies and Sebastian Gorka, Deputy Assistant to Donald Trump, I realised I'd been handling conference questions all wrong. Gorka , who is a former editor of Breitbart News, gives a virtuoso performance that illustrates every trick in the book for coming out on top in an interview: smear the questioner, distract from the question, deny the premises, and question the motives behind a difficult question. Do everything, in fact, except give a straight answer. Here's what a conference Q and A session might look like if we all mastered these useful techniques. ED: Dr Gorka, you claim that you can improve children's reading development using a set of motor exercises. But the data you showed on slide 3 don't seem to show that. SG: That question is typical of the kind of bias from people working at British Universities. You seem hell-bent on discrediting any view that doesn't agree with your own preconceived pos...