Crystal Lewis

A list of files consistently named

😍

YouTube video by Data Snacks Databot on NHANES

Trying out #Posit Databot on a dataset I know pretty well (NHANES). I do like how it helps me in my wondering about the data. It's been a while since I've recorded a video, so be gentle. #datascience #R

youtu.be/qs2GozYUUOk (Part 1)

Why is this piece of code that was fine now throwing an error? Why would it do that on a Friday afternoon? #rstats

Social Science Research Coordinator in School of Humanities and Sciences, Stanford, California, United States The Department of Psychology’s Psychophysiology Lab is seeking a full-time Social Science Research Coordinator (RC) position. The RC will be an...

The Stanford Psychophysiology Lab (PI: James Gross) is hiring a new lab manager! If you have a superstar student interested in emotion, please share this ad with them! Applications are reviewed on a rolling basis.

Job ad: careersearch.stanford.edu/jobs/social-...

#psychjobs

Do you use Positron?😉

Home Functions used for wrangling education research data - Cghlewis/data-wrangling-functions

Yes, ChatGPT can help you write #rstats code, but so can this old Wiki I created with example code used for common data wrangling needs. Who knows, you might find some gems in there.🤷‍♀️

github.com/Cghlewis/dat...

I make a Data Sources Catalog for every project I work with and I can't tell you how often the project team refers to this document to remember what measures are being collected and when. I highly recommend summarizing your plan in a simple format like this.

datamgmtinedresearch.com/dmp#dmp-cata...

Congrats on the new role!

Advances in Statistical Model Evaluation Submission deadline: 31 December 2026 The Special Issue accepts theoretical, methodological, applied, and philosophically oriented research on frequentist, Bayesian, and information-theoretic advances in statistical model evaluation.

Topics of interest for this call for papers include but are not restricted to: • Methodological advances in fit assessment, parametric bootstrapping, cross-validation, and/or other frequentist model evaluation methods • Methodological advances in prior and/or posterior predictive model checking, specification and use of informed priors, Bayes factors, and/or other Bayesian model evaluation • Methodological advances in minimum description length, normalized maximum likelihood, and/or other information-theoretic model evaluation methods • Practical applications and tutorials of advanced model evaluation methods • Philosophy of science issues underlying statistical model evaluation • Critiques/perspectives/commentaries on statistical model evaluation

Announcement: I am excited to be co-editing (with Li Cai) an upcoming Special Issue of the Journal of Mathematical Psychology on "Advances in Statistical Model Evaluation." Proposals due Feb 1. Details: www.sciencedirect.com/special-issu...

Please repost!

#quantpsych #mathpsych #philsci #statsky

RDM Weekly - Issue 022 A weekly roundup of Research Data Management resources.

Issue 22 of RDM Weekly is out! 📬

- FAIR Data Cheatsheet @w-u-r.bsky.social
- Open Research: Examples of Good Practice, and Resources Across Disciplines @ukrepro.bsky.social
- 3 Myths About Open Science That Just Won’t Die @syeducation.bsky.social
and more!

rdmweekly.substack.com/p/rdm-weekly...

Meme that says "add a small function to working code" "everything completely breaks" "remove all your changes" "code is still broken"

Hello #rstats! 👋 Do you have an #rstats package or skill or strategy you love and would be willing to share with the @rladies.org community? We are looking 👀 for a couple more speakers 🔊 for the 2025–2026 R-Ladies St. Louis season. Reply here and we will contact you to find a date! 💜 💜 💜

Introduction to anonymisation techniques for social sciences research data

⏰ One week to go until our Introduction to anonymisation techniques for social sciences research data workshop!

For more information and to book a place, please follow the link below:

📅 24 November 2025
⏰ 10:00-11:30
📍 Online
🧷 ukdataservice.ac.uk/events/intro...

We strongly suggest using the following labels: praise: Praises highlight something positive. Try to leave at least one of these comments per review. Do not leave false praise (which can actually be damaging). Do look for something to sincerely praise. nitpick: Nitpicks are trivial preference-based requests. These should be non-blocking by nature. suggestion: Suggestions propose improvements to the current subject. It’s important to be explicit and clear on what is being suggested and why it is an improvement. Consider using patches and the blocking or non-blocking decorations to further communicate your intent. issue: Issues highlight specific problems with the subject under review. These problems can be user-facing or behind the scenes. It is strongly recommended to pair this comment with a suggestion. If you are not sure if a problem exists or not, consider leaving a question. todo: TODO’s are small, trivial, but necessary changes. Distinguishing todo comments from issues: or suggestions: helps direct the reader’s attention to comments requiring more involvement. question: Questions are appropriate if you have a potential concern but are not quite sure if it’s relevant or not. Asking the author for clarification or investigation can lead to a quick resolution. thought: Thoughts represent an idea that popped up from reviewing. These comments are non-blocking by nature, but they are extremely valuable and can lead to more focused initiatives and mentoring opportunities. chore: Chores are simple tasks that must be done before the subject can be “officially” accepted. Usually, these comments reference some common process. Try to leave a link to the process description so that the reader knows how to resolve the chore. note: Notes are always non-blocking and simply highlight something the reader should take note of.

I recently discovered Conventional Comments (conventionalcomments.org) for providing a pseudo-standard set of labels for feedback and just tried it for an article review and it was really helpful to specify issues vs. thoughts vs. suggestions, etc. Hopefully it's helpful for the authors too!

Awesome! Thanks for sharing!

a cat laying on a table playing a game of magic the gathering with cards on it ALT: a cat laying on a table playing a game of magic the gathering with cards on it

Game Nite! MTG time.

Time once again to be linking to @cghlewis.bsky.social when I do my winter class that involves data analysis

Long overdue shout out for @libbyheeren.bsky.social! Recently we had some issues at one of our meetups, and being the meetup guru, Libby didn’t hesitate for a second to reach out to offer helpful advice and even make a recording of tips for future meetups for myself and co-organizers. 🙏 ❤️

Ahhh, yes, it's always tricky/scary when you are trying to share a de-identified repository.

Great resources in this list!
And I'd like to add that Data Management in Large-Scale Education Research (an open access book that also addresses data management specifically for researchers) is another good one to check out! 😊
datamgmtinedresearch.com

This is an example I've shared. Although it displays as a blank file on OSF until you download it for some reason. :/
osf.io/59gte/files/...

Ooof yeah I always recommend (if possible) never manually editing a data file, to avoid mistakes like this. :)

What's up everyone! I'm doing a Workshop for Ukraine in #rstats, I finally finished up a flyer. We'll be working on the Lotka-Volterra predator prey model. Just doing some math, coding, and making some nice visualizations. Some thoughts (1/n)

#academicsky

A Friday morning reminder to always review your raw data before you start using it (check variable types, counts, summary stats, etc.) so that you can catch fun things like rows that have been shifted. 😉

Don't make me pull out another meme. 😅

A picture of a woman reviewing a sketchpad that shows a data dictionary. With the text "The documentation we always hope we'll see when we open a repository."

I've got a question for the #medlibs...

I'm currently getting a crash course in medical claims data courtesy of Out of Pocket, and in learning about this claims process - the shape of the data via the forms, the rules that need to followed between different code systems - I'm left with the thought

I know, right? 😂

Our #IDARE team invites contributors who have existing datasets from reading intervention studies, specifically experimental studies of K-12 supplemental reading interventions!

Definitely. Usually do, just forgot here. :)

I recently came across this image and it’s a great way to summarize how I feel about my work. Whether supporting other consultants through resources or referrals, or supporting people in their data management work, helping to lift other people up benefits us all.