flynn002

How Einstein dealt with peer review: from http://theconversation.com/hate-the-peer-review-process-einstein-did-too-27405 This all started with a tweet from Jesse Shapiro under the #shareyourrejections hashtag: JS: Reviewer 2: “The best thing these authors [me and @ejalm] could do to benefit this field of study would be to leave the field and never work on this topic again.” Paraphrasing only slightly. This was quickly followed by another example ; Bill Hanage: #ShareYourRejections “this paper is not suitable for publication in PNAS, or indeed anywhere.” Now, both of these are similarly damning, but there is an important difference. The first one criticises the authors, the second one criticises the paper. Several people replied to Jesse’s tweet with sympathy, for instance: Jenny Rohn : My condolences. But Reviewer 2 is shooting him/herself in the foot - most sensible editors will take a referee's opinion less seriously if it's laced with ad hominem attacks. I took a differen...

An interesting twitter thread came along yesterday, started by this query from Jan Wessel (@wessel_lab): Quick thread of (honest) questions for the numerous people on here that subscribe to the position that sharing code in MATLAB ($) is bad open-science practice compared to open source languages (e.g., Python). What should I do as a PI that runs a lab whose entire coding structure is based (publicly shared) MATLAB code? Some say I should learn an open-source language and change my lab’s procedures over to it. But how would that work in practice?  When I resort to blogging, it’s often because someone has raised a question that has captured my interest because it does not have a simple answer. I have made a Twitter moment to store the rest of Jan’s thread and some of the responses to it, as they raise important points which have broad application. In part, this is an argument about costs and benefits to the individual scientist and the community. Sometimes these can be aligned, bu...

Helpful advice from the World Bank This blogpost was prompted by a funding call announced this week by the Economic and Social Research Council (ESRC)  , which included the following key dates: Opening date for proposals – 6 August 2018  Closing date for proposals – 18 September 2018  PI response invited – 23 October 2018  PI response due – 29 October 2018  Panel – 3 December 2018  Grants start – 14 February 2019  As pointed out by Adam Golberg (@cash4questions), Research Development Manager at Nottingham University, on Twitter, this is very short notice to prepare an application for substantial funding: I make this about 30 working days notice. For a call issued in August. For projects of 36 months, up to £900k - substantial, for social sciences. With only one bid allowed to be led from each institution, so likely requiring an internal sift.  I thought it worth raising this with ESRC, and they replied promptly, saying: To access funds for this c...

Yesterday I had the pleasure of hearing George Davey Smith (aka @mendel_random) talk. In the course of a wide-ranging lecture he recounted his experiences with conducting a systematic review. This caught my interest, as I’d recently considered the question of literature reviews when writing about fallibility in science . George’s talk confirmed my concerns that cherry-picking of evidence can be a massive problem for many fields of science. Together with Mark Petticrew, George had reviewed the evidence on the impact of stress and social hierarchies on coronary artery disease in non-human primates. They found 14 studies on the topic, and revealed a striking mismatch between how the literature was cited and what it actually showed. Studies in this area are of interest to those attempting to explain the well-known socioeconomic gradient in health. It’s hard to unpack this in humans, because there are so many correlated characteristics that could potentially explain the association. The pr...

At a recent conference, someone posed a question that had been intriguing me for a while: suppose you have limited resources, with the potential to test N participants. Would it be better to do two studies, each with N/2 participants, or one big study with all N? I've been on the periphery of conversations about this topic, but never really delved into it, so I gave a rather lame answer. I remembered hearing that statisticians would recommend the one big study option, but my intuition was that I'd trust a result that replicated more than one which was a one-off, even if the latter was from a bigger sample. Well, I've done the simulations and it's clear that my intuition is badly flawed. Here's what I did. I adapted a script that is described in my recent slides that give hands-on instructions for beginners on how to simulate data, The script, Simulation_2_vs_1_study_b.R , which can be found here, generates data for a simple two-group comparison using a t-test. In...

 Doing research, analysing the results, and writing it up is a prolonged and difficult process. Submitting the paper to a journal is an anxious moment. Of course, you hope the editor and reviewers will love it and thank you for giving them the opportunity to read your compelling research. And of course, that never happens. More often you get comments from reviewers pointing out the various inadequacies of your grasp of the literature, your experimental design and your reasoning, leading to further angst as you consider how to reply. But worse than this is silence. You hear nothing. You enquire. You are told that the journal is still seeking reviewers. If you go through that loop a few times, you start to feel like the Jane Austen heroine who, having dressed up in her finery for the ball, spends the evening being ignored by all the men, while other, superficial and gaudy women are snapped up as dance partners. There have been some downcast tweets in my timeline about papers getting ...

Source: http://www.weblogcartoons.com/2008/11/23/ideas/ Those of you who follow this blog may have noticed a lack of thematic coherence. I write about whatever is exercising my mind at the time, which can range from technical aspects of statistics to the design of bathroom taps. I decided it might be helpful to introduce a bit of order into this chaotic melange, so here is a catalogue of posts by topic. Language impairment, dyslexia and related disorders The common childhood disorders that have been left out in the cold (1 Dec 2010) What's in a name? (18 Dec 2010) Neuroprognosis in dyslexia (22 Dec 2010) Where commercial and clinical interests collide: Auditory processing disorder (6 Mar 2011) Auditory processing disorder (30 Mar 2011) Special educational needs: will they be met by the Green paper proposals? (9 Apr 2011) Is poor parenting really to blame for children's school problems? (3 Jun 2011) Early intervention: what's not to like? (1 Sep 2011) Lies, damned li...