rpodcast, 21 days ago to datascience

Episode 163 the @rstats @rweekly Highlights Podcast is out! https://serve.podhome.fm/episodepage/r-weekly-highlights/issue-2024-w18-highlights

🔁 What's new in R 4.4.0 @haematobot @jumpingrivers
📝 Add {bslib} to your #shinyapp snippets @grrrck @Posit
✨ Tailoring Shiny for modern users (Lindsay Jorgenson) & @jdatap

R Weekly is powered by the community. Visit https://rweekly.org to share new resources to the project via a pull request. Plus you can send your hosts a boost on the Podcast Index!

h/t @mike_thomas 🙏

#RStats #DataScience #V4V

Ifeanyi5, 2 months ago to random

Please, what is the latest with regards to ShinyLive? Can it now load and run all R packages? Also, is it now possible to deploy a Shiny app built using ShinyLive?

#rstats #shiny #shinyapp #shinylive

jrboehnke, 7 months ago to random

One of the most problematic areas in the submission we get and papers I review are the sections on #SampleSize justifications.

See for example @lakens' excellent paper on the topic:
https://psyarxiv.com/9d3yf/
It now comes with a process guide in a #ShinyApp, which is an excellent support:
https://shiny.ieis.tue.nl/sample_size_justification/
#Rstats

For #HRQL researchers:
https://rdcu.be/dnfO4

And many people teach this stuff, e.g., ☺️
https://www.researchgate.net/publication/335813329_Estimating_sample_sizes_based_on_required_precision_for_surveys_and_epidemiological_research

#StudyDesign #NightshifEditor

SNL_Luebeck, 11 months ago to science German

New comment on #RethinkFunding including the #shinyapp #GrantInq published!

https://www.nature.com/articles/s41562-023-01649-y

Research funding determines the course of science and thus shapes future knowledge. However, funding allocation is inherently biased, non-optimal and
costly. We present a Shiny app that simulates the effects of funding scenarios on #costs, #diversity and #quality. We advocate a #lottery at the beginning to promote inclusion.

#funding #science #research #bias
@rmrahal