Sarah F. Pedonti
@sarahpedonti.bsky.social
730 followers 870 following 100 posts
Asst. prof in early childhood education, special education, early literacy, STEM & language development. Developmental thinker and doer. Rstats enthusiast, outdoor learning. Teacher. Mom.
Posts Media Videos Starter Packs
Reposted by Sarah F. Pedonti
robertkelchen.com
ED is requesting public comments on the direction that they should take the Institute of Education Sciences. Feedback is due October 15.

public-inspection.federalregister.gov/2025-18608.pdf
public-inspection.federalregister.gov
sarahpedonti.bsky.social
Anybody else on here read the new ACF email yet? Can we get a support group going?
sarahpedonti.bsky.social
This was also true at the Society for Research in Child Development in May.
dannagal.bsky.social
You’re think *you’re* depressed? Try being at the annual meeting of the American Political Science Association right now with 5,000 political scientists presenting their work on the state of democracy, public opinion, and media.

They are also drinking heavily.
Reposted by Sarah F. Pedonti
dannagal.bsky.social
You’re think *you’re* depressed? Try being at the annual meeting of the American Political Science Association right now with 5,000 political scientists presenting their work on the state of democracy, public opinion, and media.

They are also drinking heavily.
sarahpedonti.bsky.social
Super cool paper for anyone who’s ever worked with non-normal data or run am interaction model and struggled to describe the effect!
dingdingpeng.the100.ci
Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities

Abstract
Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models).
Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve. A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals).

Illustrated are 
1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals
2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and
3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
sarahpedonti.bsky.social
Are all faculty everywhere still PDFing every acceptance letter and email, or has someone invented a better way to do this tenure dossier thing yet? thinking being able to forward emails to [email protected] and get a nicely zipped set of folders +attachments sounds like a great biz idea.
sarahpedonti.bsky.social
Thank a farmworker! ¡Gracias, campesinos! 🍅
thetnholler.bsky.social
ALABAMA: “The verdict is in. The state’s tough immigration law just isn’t working out… American workers not mentally or physically fit enough to last one day…”
sarahpedonti.bsky.social
Here's what AI has to say about what $200 million could buy taxpayers besides a golden freaking ballrooom.
Reposted by Sarah F. Pedonti
jim-robinson.bsky.social
@tll6601.bsky.social @pirkkoelf.bsky.social @stanzucker.bsky.social @sarahpedonti.bsky.social @alexandrashelton.bsky.social @drdpaweston.bsky.social #EduSky

🙏 Seeking participants for dissertation survey on social inclusion for students w/ Autism- Please consider reposting! #EduSky
jim-robinson.bsky.social
Hello everyone!

I am working on my dissertation, & my topic focuses on the social inclusion of students with autism in elementary schools. Please consider taking the survey below, & sharing it with any other educators/ administrators that you may know.

Tinyurl.com/SocialInclusionASD
sarahpedonti.bsky.social
There’s no time like the first week of summer vacation for a dedicated fourth grader to learn to whistle.
sarahpedonti.bsky.social
Love this- now it’s pointed me to your videos, which I plan to share with undergraduates!
sarahpedonti.bsky.social
My brothers and sisters in Christ: this is why we need academics (or just people with basic statistical training) more than ever.
oalexanderdk.bsky.social
I don't know what is funniest.

The fact that their Y axis goes to 120%, them not being able to sort the dates properly, or the approval rating that would make Kim Jong Un blush.
Reposted by Sarah F. Pedonti
srcdorg.bsky.social
Federal research funding cut? Don’t stop now.
Two quick-response grants can help:
Spencer Foundation – bridge funding for education researchers: bit.ly/4jvA7oi
RWJF – racial & Indigenous health equity research support: bit.ly/44VUJ4D
#SRCD #ChildDevelopment
sarahpedonti.bsky.social
wonderful time with great colleagues (new and old) at #SRCD2025. Thankful for everyone practicing joy as resistance and speaking truth to power right now.
Reposted by Sarah F. Pedonti
byrdnick.com
A #criticalThinking exercise reduced Dems' #fakeNews sharing intent, but not Reps' (N > 1k).

CT exercise: answer 3 questions (with an alluring-but-false option), and then read correct answers, explanations, and instructions to think more reflectively.

🔓 doi.org/10.1007/s121...
Fig. 3 The interaction effect of cognitive style and political identity on intention to share fake news. Note. The score indicators on the Y-axis, representing intention to share levels, were truncated in 0.1 increments
sarahpedonti.bsky.social
The irony of this comment when Tillis sounds like Foghorn Leghorn and Weezer from Steel Magnolias had a baby.
Reposted by Sarah F. Pedonti
wishda.bsky.social
They are hooking all this info up to AI. They don’t have the manpower to go through this themselves.

Comply with fouled data. Project numbers and incoherent descriptions that lack obvious key terms for AI to look over. Brag about yourself endlessly without ever getting to the points.

Be academics.
Reposted by Sarah F. Pedonti
dcollier74.bsky.social
Part of the reason I blasted AEI at AEFP.

Them, CATO, Heritage, Manhattan, and others engaged in a decades long public attack on #HigherEd with garbage research - like very basic/shitty ROI work or made up shit about student loans. Then DC, Ivy League educated reporters platformed them + still do.
Reposted by Sarah F. Pedonti
wwr.bsky.social
Kevin, I would like to suggest that future finance historians call this stock market collapse “The Orange Crush.”

Thank you in advance.
Reposted by Sarah F. Pedonti
taniel.bsky.social
If you’re a North Carolinian, you can check whether your name or the names of anyone you know is on the list of the 65K voters whose votes may be tossed. You could have an opportunity to fix it if so.

thegriffinlist.com
Reposted by Sarah F. Pedonti
triangleblogblog.bsky.social
Hello! We are a scrappy three-year-old civics blog based in Chapel Hill and Carrboro, NC.

We just updated
thegriffinlist.com, which contains detailed instructions for 65,000 NC voters whose votes might be thrown out in the state Supreme Court race. Please share!
The Griffin List
A list of 60,273 North Carolina voters – these are registered voters who showed ID to early vote in the November 2024 election – whose votes Jefferson Griffin wants to not be counted. ...
thegriffinlist.com