Next week I will be presenting my work at Institut De l'Audition in Paris, at Universität Oldenburg (Germany), at Technical University of Denmark, then back home. I will travel only by train, in a desperate attempt to reduce the carbon footprint of research. This is a bit of an adventure, though: 600€ in train tickets and a total travelling time of 26h...
The #bayesian learning party continues with my brms / tidyverse #rstats translation of Bayes Rules chapter 15 introducing hierarchical/multilevel models. Nothing too fancy in this chapter—it does an excellent job comparing pooling/no pooling/partial pooling https://bayesf22-notebook.classes.andrewheiss.com/bayes-rules/15
It's reassuring to know that despite the perverse incentives, despite the crooked publication system, science does actually contain the tools to evaluate its own weaknesses, and maybe to heal itself. (3/3)
A particularly enlightening insight is the estimation of the prevalence of fraud (e.g. how often do biologists fake the figures in their papers?), publication bias, p-hacking, and even numerical errors in published papers... There are public records (such as Retraction Watch), very clever tools (such as statcheck http://statcheck.io/), and tests (e.g. the GRIM test https://en.wikipedia.org/wiki/GRIM_test) (2/3)
I just finished Stuart Ritchie's jaw-dropping book "Science Fictions" which exposes the deleterious effects of fraud, bias, negligence and hype on the constitution of scientific knowledge. Of course this is a a deplorable but all-too-familiar observation, however the book brings a new level of detail. (1/3)
Did you know that my sample size justification paper (which you are citing about once a day, thanks for that) has a shiny app that will guide you towards a state of the art sample size justification? You can find it here: https://shiny.ieis.tue.nl/sample_size_justification/ As part of this Mastodon promotion month, I will answer each and every question anyone has who uses the Shiny app for the sample size justification in their next study (if I can!).
A toot-summary of our recent article!
We often use our confidence to gauge the reliability of our perception.
But what about the confidence... in our confidence?
Sometimes, we can be certain we are uncertain.
With Samuel Recht, Ljubica Jovanovic, and Pascal Mamassian, we had fun testing the limits of meta-metacognition in a classic visual task.
We found surprising accuracy of confidence up to the fourth order (confidence in confidence in confidence, or meta-meta-meta-cognition).
https://www.radiofrance.fr/franceculture/podcasts/la-science-cqfd/metoo-la-science-aussi-9608803
Un épisode très dense de #scienceCQFD sur les inégalités et violences de genre dans les sciences. Parmi les nombreuses choses qui y sont dites, cette réflexion de Marianne Blanchard lorsque le débat commence à s'orienter exclusivement sur la lutte contre les biais de genre : "Il ne faut pas non plus se focaliser sur ces stéréotypes... Le risque est de diluer les responsabilités. Ils sont une conséquence de rapports de pouvoir sociaux de sexe. Il y a des fondements matériels, et des réalités sexistes et sexuelles."
Hello #fediverse! As seems to be the tradition, here is my #introduction
I am a French #CNRS researcher working on #speechperception, #psychophysics, #statistics and #audiology (mostly). I write scientific articles in English (http://dbao.leo-varnet.fr/publications/) and blog posts in French (http://dbao.leo-varnet.fr/) so I'm always confused about which language I should use on social media...
Happy to start my #twittermigration by connecting with academics and people interested in science here!
CNRS researcher at École normale supérieure Paris. Auditory perception, psycholinguistics, hearing loss. My toots are searchable #tootfinder.