useR! - The R User Conference

Great news, useR! is coming back! Sign up today to receive notifications about conference announcements! useR! 2025 will be held from Friday, August 8th to Sunday, August 10th at Duke University in Durham, NC, USA. More details will be announced shortly, so stay tuned! useR! is an annual international conference for users and developers of the R programming language. It's organized by the R community and supported by the R Foundation. The conference showcases applications and developments of R software, featuring presentations, workshops, and discussions on various R-related topics. It's a great opportunity for R users to learn, share knowledge, and network with others in the community. #rstats #datascience #coding #rlanguage #statistics #computing #opensource #softwareengineering #data #analytics #data #research

SAVE THE DATES!!! Great news: useR 2025 will take place at Duke University, in Durham, NC, USA, August 8-10! More details to announced shortly, so stay tuned #rstats #datascience #coding #rlanguage #statistics #computing #opensource #softwareengineering #data #analytics #data #research

SAVE THE DATES!!! Great news: useR 2025 will take place at Duke University, in Durham, NC, USA, August 8-10! More details to announced shortly, so stay tuned #rstats #datascience #coding #rlanguage #statistics #computing #opensource #softwareengineering #data #analytics #data #research

Missing Data Exploration, Imputation, and Evaluation Missing data are ubiquitous, pervasive, and often ignored in statistical analyses. Unfortunately, default methods such as complete case analysis may lead to biased and invalid results. This hands-on tutorial aims to equip data analysts with knowledge and skills to validly handle missing data using the popular R package {mice}. Hanne Oberman 🟥, Utrecht University #rstats #coding #opensource #data #dataanalytics #rainbowR #datascience #r #rlanguage #analytics https://lnkd.in/eYvz_SqA

"Stop Making Spaghetti (Code)" presented online at UseR! 2024 by Nicola Rennie, Lecturer in Health Data Science https://lnkd.in/e3_t4fc4 With an increasing number of academic journals requiring authors to submit code, an increasing number of PhD students developing R packages, and more open source packages requiring maintenance, the list of R programming skills required of new quantitative PhD students is ever growing. Many of these PhD students don’t have backgrounds in computer science, but find themselves writing code and developing software on a daily basis. They don’t always have supervisors with backgrounds in computer science either. So how do we help students go from writing spaghetti code, to working with good software development practices? In this talk, I’ll outline what training is currently offered to PhD students, gaps that have been identified (often by students themselves), and a suggestion of how we can better prepare PhD students for quantitative research so that none of them say “If I knew then what I know now, I would have done things entirely differently.” Nicola Rennie is a Lecturer in Health Data Science based within the Centre for Health Informatics, Computing, and Statistics at Lancaster Medical School. Her research interests include applications of statistics and machine learning to healthcare and medicine, communicating data through visualisation, and understanding how we teach statistical concepts. Nicola can often be found at data science meetups, presenting at conferences, and is the R-Ladies Lancaster chapter organiser. #rstats #coding #opensource #data #dataanalytics #rladies #datascience #r #rlanguage #analytics

What is it about R that inspires such love, devotion, and creativity in us? This talk is an affectionate journey through the many things that make R and her community gloriously weird. We’ll dip our toes into the history of programming to learn more about the unusual structures and aspects of the R language that send computer scientists spinning: dynamic environments, first-class functions, S3 classes, nonstandard evaluation, and so on. At the same time, we’ll explore some of the quirky and unique elements of the R community that keeps it fresh, exciting, and welcoming to new users. Finally, we’ll reflect on what it’s going to take to sustain this special language and community and to keep the R magic alive. Kelly Bodwin Associate Professor of Statistics and Data Science, Cal Poly https://lnkd.in/g_XNQpK2 #RStats

Want to effectively build Shiny apps, so that extending and maintaining them is not a burden? Test-driven development is a proven method of building such code. It also provides us: → with fast development cycles, → a better understanding of the problems we're solving, → and confidence that our code works as expected. To get started with TDD, check out the recording of my talk from useR! - The R User Conference: https://lnkd.in/dih8Yn3i #RStats #RShiny #RDevelopment #RStudio #Tests #Testing #useR2024 #useR

I'm happy to share that the talk about the #R package #pencal that I presented at useR! - The R User Conference in July is now available on Youtube: https://lnkd.in/eTKYWktr This was my first time at a UseR! conference. It was real fun to attend it, and an honour to have the opportunity to present in front of such a large and global audience! #Rstats #statistics #machineLearning #software #prediction #survival

"How Your Code Might Get Rusty, And What You Can Do About This" - Keynote at useR! Conference 2024 given by Maëlle Salmon. https://lnkd.in/eERUD4eY Title: How Your Code Might Get Rusty, And What You Can Do About This Speaker: Maëlle Salmon, Cynkra & rOpenSci Abstract:  Do you ever find yourself working on a codebase that has gotten a bit rusty over time? Or read an old script and have trouble understanding what it does? It happens to me regularly, be it code that I wrote myself, or code I was tasked with, such as the established igraph R package. In this talk, I share some of my strategies to suffer less when renovating a codebase, as well as prevention ideas to make future renovations less likely, or easier. I also discuss the human challenges of software maintenance, based on observations of the federation of maintainers that we try to nurture at rOpenSci. Maëlle Salmon, with a PhD in statistics, is a Research Software Engineer and blogger. At rOpenSci, she maintains the guide “rOpenSci Packages: Development, Maintenance, and Peer Review,” and has developed the babeldown and babelquarto packages for multilingual documents. At cynkra, she contributes to the fledge and igraph packages. Maëlle is also the co-author of the book “HTTP testing in R” with Scott Chamberlain and manages the R-hub blog. Additionally, she regularly contracts with various organizations, including research institutions, for R package development. Maëlle is a member of the R-Ladies Global team.

There were many surprises at #useR2024, Salzburg, last July. One of them was that different software has different result values for operations (for example, round(0.5)) I had experienced something similar in a previous "SAS to R conversion project" and thought “That's weird.. 🤨”, but it turns out that it takes quite a bit of effort. Chi Zhang's presentation and help gave me the opportunity to learn more about this “baseline” project called #CAMIS and contribute to the #Rbloggers about it.  Like many open source projects, this #CAMIS project needs a lot of attention, support, and contributions, and if you love #Rstat and #Quarto, there's a lot to be excited about. Thanks again to Chi Zhang and the other members for their dedication to the project. You can check article with below link 🤭 https://lnkd.in/gkTEndyJ