Lukas Beinhauer @LBnhr@qoto.org
stats & programming | meta-analysis & heterogeneity in (wild) Psychology
he/him
Joined Nov 2022
Preprint updated because actually submitted - we discuss why differences in reliability might not actually inform you about differences in measuring quality - and what to do instead!
Get the full story at https://osf.io/preprints/psyarxiv/ud9rb
Lukas Beinhauer
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Happy to announce I'm teaching a summer school on cutting edge #metaanalysis using open source software, from basics up to machine learning methods for exploring heterogeneity, icw
MethodsNET at @Radboud_uni https://www.ru.nl/en/education/education-for-professionals/overview/meta-analysis-rss217
Similarly, if anyone is aware of a literature search tool that allows for selection based on data being openly available, that would be great as well! Like a Googe Scholar, EBSCOhost etc. where I can select for the presence of open data
Anything that goes in similar directions also helps! I'm aware of typical ManyLabs and Registered Replication Report stuff, but systematical variation in either outcome measure (psychometric scale etc.) or the treatment, manipulation, intervention etc. has been coming up short unfortunately
I'm searching for open replication data! Conceptual replications employing either:
- same treatment/intervention but different outcome measure
or:
- different treatment (dose)/intervention but identical outcome measure
(or both)
Any pointers appreciated!
Sometimes, to distinguish a population parameter from an observed estimate, the term "true" is used. For example, sometimes researchers use "true mean" to distinguish the population mu (greek \mu) from the sample mean (x-bar).
In classical test theory, we use "true score" to distinguish between an observed score, that contains error, and the score that we should have gotten if no measurement error was involved.
In order to properly distinguish the two types of "true-ness", is there another adjective I could use for the first case, the population mu (greek \mu)?
Lukas Beinhauer
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The @DataColada team has been sued by Francesca Gino for exposing the fraudulent data underlying four of her papers (she claims defamation). The legal defense could get expensive. Please join us in providing financial support for their defense.
Lukas Beinhauer
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There is a GoFundMe to help the @datacolada team with the legal costs of being sued by Francesca Gino: https://gofund.me/58491686
If you can, chip in!
@JFuenderich, @epizyklen@nerdculture.de and I would love to discuss standardisation practices with you in Padua (or remote). The video is on osf: https://osf.io/eab9u or, including subtitles, on YouTube: https://youtu.be/tRveDihxtfM
Going to #SIPS2023, but unsure what unconference to visit? Go ahead and give our very brief (5 min!) ramp-up video on standardisation practices in Psychology a watch! @improvingpsych
Lukas Beinhauer
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We consider all research should be immediately available #OpenAccess, regardless of whether it was publicly funded or privately funded.
Lukas Beinhauer
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🚨Psych-DS is hiring! 🚨
We are looking for a software engineer to build validation tools (Python, R, Javascript/client side browser) for a technical specification/data standard for behavioral datasets
Details in thread, application here: https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails/jobDetail.html?jobPostId=27058&localeCode=en-us&source=Indeed&sourceType=PREMIUM_POST_SITE
@JFuenderich @epizyklen@nerdculture.de
And here the actual Tutorial:
https://www.youtube.com/watch?v=fc9c7hiqnXE
@JFuenderich @epizyklen@nerdculture.de
Now on Youtube:
https://www.youtube.com/watch?v=BPfiQkwjqX8&t=635s
Lukas Beinhauer
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On March 30th 1867, Alaska was purchased from Russia for 7.2 million $. Today we present to the internet: Our totally free framework to harmonize & analyze multi-lab data! Thanks for having us at #ESMARConf #eshackathon
See here on #youtube: https://www.youtube.com/watch?v=m-W8O2yhReg
Also, check out our preprint: https://psyarxiv.com/bcpkt/
Trouble dealing with meta-scientific replication data? There's still time to register for #ESMARConf2023 and catch our tutorial on MetaPipeX - a novel framework, R-package and shiny app to make multi-site replication data more accessible!
You don't want to miss it!
Most work is done by
@JFuenderich - @epizyklen@nerdculture.de and my fabulous personality show up mostly to spice up the tutorial!
Lukas Beinhauer
boosted
Preprint Alert!
Computational Reproducibility is hard work, multi-labs are hard work. We propose a standardized framework to deal with analyses for group comparisons ins multi-labs. Featuring: An R-package and a Shiny App!
Read all about it at https://psyarxiv.com/bcpkt/
@LBnhr @epizyklen
Preprint alert!
My fantastubular colleague has been working on a standardized framework to deal with meta-analyses in multi-lab-style data!
Lukas Beinhauer
boosted
In Utrecht, NL people have been falling into a pond because duckweed has been stressed by the cold and turned it red an looks exactly like a cycle path.
stats & programming | meta-analysis & heterogeneity in (wild) Psychology
he/him
Joined Nov 2022
