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Tiffany Wu

@tiffanyxwu.bsky.social

16 Posts855 Follower 528 Folgt

Yiqing Xu @yiqingxu.bsky.social · 5mo ago

On panelView, and why we should always look at our data first.. yiqingxu.substack.com/p/plot-your-...

Please look at your (panel) data

Many of the most egregious issues can be avoided by simply looking at the data.

yiqingxu.substack.com

Ambassador Frank Hull @frankiethull.bsky.social · 7mo ago

University of Michigan Gerald R. Ford School of Public Policy @fordschool.bsky.social · 8mo ago

@tiffanyxwu.bsky.social, an EPI postdoctoral fellow, was recently featured in an Education Week article on academic absenteeism. Read the full story: https://myumi.ch/9pMwX

Should schools lower the chronic absenteeism threshold? New EPI research suggests they should

New evidence from the Ford School's Education Policy Initiative (EPI) shows absenteeism may hurt student's academics long before it is considered a chronic pattern. These findings, published in a Janu...

myumi.ch

Anton Strezhnev @astrezh.bsky.social · 9mo ago

The Spring 2026 course website for my grad causal inference class is up and running. Was inspired by @andrew.heiss.phd and @mattblackwell.bsky.social to move my materials over to a standalone site and use as little of Canvas as possible. www.antonstrezhnev.com/ps813/

PoliSci 813

antonstrezhnev.com

Betsy Wolf @betsyjwolf.bsky.social · 9mo ago

Curious about what people said in response to the RFI about "re-imagining" the Institute of Education Sciences (IES)? I put the public comments in one file (763 pages) and used AI to analyze the themes and areas of agreement and disagreement (5 pages) by audience ⬇️: docs.google.com/document/d/1...

Loading Google Docs

Web word processing, presentations and spreadsheets

docs.google.com

Richard McElreath 🐈‍⬛@rmcelreath.bsky.social · 10mo ago

I'm teaching Statistical Rethinking again starting Jan 2026. This time with live lectures, divided into Beginner and Experienced sections. Will be a lot more work for me, but I hope much better for students. I will record lectures & all will be found at this link: github.com/rmcelreath/s...

course schedule as a table. Available at the link in the post.

Julia M. Rohrer @dingdingpeng.the100.ci · 10mo ago

Just gave my last talk of the year! 2025 was quite packed, I gave talks about: - the age-period-cohort problem - making rigorous causal inference more mainstream - mediation analysis - marginaleffects - causal graphs (x10) If you're curious, check out my slides here: juliarohrer.com/resources/

Resources

Here you can find a collection of things that may be helpful, including slide decks, a curated list of introductory papers and blog posts, as well as some infographics I have generated to explain v…

juliarohrer.com

Posit @posit.co · 10mo ago

New data from @sara-altman.bsky.social & @simonpcouch.com, using the vitals and ellmer packages, looks at LLM performance metrics for #RStats. 👀 Sneak peek: Claude Opus 4.5, Claude Sonnet 4.5, & OpenAI GPT-5 lead in generating correct R code. Read the full breakdown: posit.co/blog/r-llm-e...

Which LLM writes the best R code? - Posit

The vitals package delivers a dedicated framework for measuring how well Large Language Models perform with code.

posit.co

Paul Bruno @paul-bruno.com · last yr.

The Relationship Between Student Attendance and Achievement, Pre- and Post-COVID journals.sagepub.com/doi/abs/10.1...

Sage Journals: Discover world-class research

Subscription and open access journals from Sage, the world's leading independent academic publisher.

journals.sagepub.com

Aaron Sojourner @aaronsojourner.org · 2y ago

We invest 9X less per child-year in care & education in the first 5 years of life than the next 13. This gap in public investment is why K12 is free for parents & early care & education is expensive. www.hamiltonproject.org/publication/...

Shaun M. Dougherty @doughesm.bsky.social · last yr.

🚨Interested in a PhD focusing on quant methods and education & social policy? I'm recruiting this year at @bclynchschool in the Measurement, Evaluation, Statistics, and Assessment program www.bc.edu/bc-web/schoo...

Doctor of Philosophy (Ph.D.) in Measurement, Evaluation, Statistics, and Assessment - Lynch School of Education and Human Development - Boston College

MESA has been training students to examine educational programs, design quantitative research studies, develop assessment instruments, and analyze educational data to help inform policy-making for ove...

bc.edu

Annenberg Institute @annenberginstitute.bsky.social · last yr.

📢 #EdWorkingPapers: How can we measure student behavior at scale? @tiffanyxwu.bsky.social, @weilanch.bsky.social, @mattadiemer.bsky.social, Rebecca Unterman, @annakshapiro.bsky.social, & Thomas Staines use PCA and factor analysis to build behavior composites from admin data. 📄 bit.ly/4ofre5b

Joshua Goodman @joshua-goodman.com · last yr.

🔥What’s the only thing hotter than this week’s weather?🔥 Our new @wheelockpolicybu.bsky.social working paper: “School Enrollment Shifts Five Years After the Pandemic” In it, BU Wheelock PhD @abbyfrancis.bsky.social and I ask: Has the pandemic permanently changed families' schooling choices?

Paul Bruno @paul-bruno.com · last yr.

If we're heading into summer that means academic job market season is looming. As a reminder, my collected tips are here (along with my standing offer to set up time to chat with folks): www.paul-bruno.com/2021/07/tips...

Some Basic Tips About the Academic Job Market – Paul Bruno

paul-bruno.com

Joshua Goodman @joshua-goodman.com · last yr.

Re-upping my advice about how to write a good title and abstract for an academic paper, appropriately called: "How to Write a Title and Abstract" Feel free to share this thread, which will focus on titles. #EconSky #AcademicSky

Tiffany Wu @tiffanyxwu.bsky.social · last yr.

🤔 What kind of Pre-K experience sets students up for long-term success? Our new working paper offers important new evidence to help answer this question! 🔗 edworkingpapers.com/sites/default/files/ai25-1194.pdf And 🧵👇

A screenshot of the abstract of the working paper

Figure 1: School Enrollment Pathways for Lottery Winners and Control Group Students through 8th Grade. This figure represents school enrollment pathways across different school types (BPS, BPS Exam School, non-BPS district school, charter school, and other) for both lottery winners and the control group. The thickness of the lines represents the percentage of lottery winners/control group students that are enrolled in each type of school. Blue lines show the pathways taken by lottery winners, and BPS-specific school categories are highlighted in the light blue boxes. BPS = Boston Public Schools.

Annenberg Institute @annenberginstitute.bsky.social · last yr.

🚀 Launching the EdWorkingPapers Policy & Practice Series! Too much good research never reaches the people making real decisions. Our new series changes that. Each 2-pager highlights key findings from #EdWorkingPapers, made for busy leaders and policymakers. 📄 Read the first three: bit.ly/3Z1Kok2

Christina Weiland @weilanch.bsky.social · last yr.

Using data from Michigan, we find that third grade retention for struggling readers may be a much less important component of the benefits of literacy reforms than previously understood. (Thx, @annenberginstitute.bsky.social, for the dissemination bump!)

Annenberg Institute@annenberginstitute.bsky.social · last yr.

📢 #EdWorkingPapers: Flagged for retention, but not retained: Michigan’s 3rd-grade retention policy raised reading scores largely by triggering extra help, not holding kids back. 🔍Jordan Berne, Brian Jacob, @weilanch.bsky.social, Katharine Strunk 📄 edworkingpapers.com/ai25-1188

John Holbein @johnholbein1.bsky.social · last yr.

Wow! Each $1 spent on Universal Pre-Kindergarten generates between $3-$20 dollars in aggregate earnings. That's enough to offset the costs of Universal Pre-Kindergarten through higher tax revenues.

Andrew Heiss @andrew.heiss.phd · last yr.

Thing I just learned in #rstats: unz() lets you connect to a .zip and load files from inside it without actually unzipping it (great for a file I'm working with that's 30 MB zipped and 1+ GB unzipped, with multiple CSVs in it)

# unz() lets you connect to a .zip and treat it like a mini file system,
# and you can load files from inside it
one_zipped_csv_among_others <- readr::read_csv(
unz("lotsa_zipped_csvs.zip"), "one_csv.csv"
)

# readr::read_csv() can read a .zip with a single CSV in it
one_zipped_csv <- readr::read_csv("big_zipped_file.zip")

chloe gibbs @chloergibbs.bsky.social · last yr.

I hope it is not lost, in all of the chaos at the federal level, that there are many longstanding, discretionary programs that are on the Administration's chopping block, either directly or through the erosion of agency staff, expertise, and capacity. Programs enacted and reauthorized through...

Vincent Arel-Bundock @vincentab.bsky.social · 2y ago

📚😅🎉 Yay!! I just submitted the complete manuscript of my upcoming book to the publisher! Learn to easily and clearly interpret (almost) any stats model w/ R or Python. Simple ideas, consistent workflow, powerful tools, detailed case studies. Read it for free @ marginaleffects.com #RStats #PyData

Model to Meaning: How to interpret statistical models with marginaleffects for R and Python

Andrew Heiss @andrew.heiss.phd · 2y ago

I’ve long used FiveThirtyEight’s interactive “Hack Your Way To Scientific Glory” to illustrate the idea of p-hacking when I teach statistics. But ABC/Disney killed the site earlier this month :( So I made my own with #rstats and Observable and #QuartoPub ! stats.andrewheiss.com/hack-your-way/

Screenshot of the linked Quarto website, with input checkboxes to change different conditions for a regression model that predicts economic performance based on US political party, with a reported p-value

Prof Dynarski @dynarski.bsky.social · 2y ago

If you have research dependent on these data here is my suggestion 1/N Big picture: Create a dataset of cell means (cells must be big enough to pass disclosure) - load these cell means into many, many tables & put through review -These cell means can then be used in OLS - which runs on means

Andrew Ho@andrewdeanho.bsky.social · 2y ago

Research with restricted-use data is more precise, powerful, and relevant. Faculty and staff will be working through the weekend to answer important research questions before we no longer can. This is not normal, necessary, or efficient.

Cara Jackson @carajackson.bsky.social · 2y ago

Objective, comprehensive, rigorous, timely, and useful: A digital hub for evidence-based education policy research. #EdResearch #EdPolicy livehandbook.org

Evidence-Based Education Policy Research | Live Handbook

Explore evidence-based education policy research at our digital hub. Access data-driven insights to improve learning outcomes and shape effective policies.

livehandbook.org

Andrew Heiss @andrew.heiss.phd · 2y ago

New preprint! A general overview of stats in public policy research with this (oversimplified but still helpful) separation of methods into description, explanation, and prediction #policysky HTML/PDF: stats.andrewheiss.com/snoopy-spring/ SocArXiv: doi.org/10.31235/osf...

This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century. I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations. I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field.

Description Explanation Prediction
General question What exists? Why does it exist? How can it be influenced? What will happen next?
Focus of analysis Focus is on any variable—understanding different variables and their distributions and relationships Focus is on X —understanding the relationship between X and Y, often with an emphasis on causality Focus is on Y —forecasting or estimating the value of Y based on X, often without concern for causal mechanisms
Names for variable of interest — Explanatory variable
Independent variable
Predictor variable
Covariate Outcome variable
Dependent variable
Response variable
Goal of analysis Summarize and explore data to identify patterns, trends, and relationships Estimation: Test hypotheses or theories and make inferences about the relationship between one or more X variables and Y

Causal attribution: A special form of estimating—make inferences about the causal relationship between a single X of interest and Y through credible causal assumptions and identification strategies Generate accurate predictions; maximize the amount of explainable variation in Y while minimizing prediction error
Evaluation criteria — Confidence/credible intervals, coefficient significance, effect sizes, and theoretical consistency Metrics like root mean square error (RMSE) and R^2; out-of-sample performance
Typical approaches Univariate summary statistics like the mean, median, variance, and standard deviation; multivariate summary statistics like correlations and cross-tabulations t-tests, proportion tests, multivariate regression models; for causal attribution, careful identification through experiments, quasi-experiments, and other methods with observational data Multivariate regression models; more complex black-box approaches like machine learning and ensemble models

Table of contents
Introduction
Brief history of statistics in public policy
Core methodological approaches
Description
Explanation
Prediction
The pitfalls of counting, gathering, and learning from public data
Future directions
References

Beth Schueler @bethschueler.bsky.social · 2y ago

It's that time of year to circulate this list of orgs for those seeking ed policy jobs/internships. Please let me know if there are opportunities/orgs I should add. Good luck out there! docs.google.com/spreadsheets...

The Unofficial List of Ed Policy Orgs for Job/Internship Seekers

docs.google.com

Nick Huntington-Klein @nickchk.com · 2y ago

After a long wait, the working paper for the Many-Economists Project: The Sources of Researcher Variation in Economics. We had 146 teams perform the same research three times, each time with less freedom. What source of freedom leads to different choices and results? papers.ssrn.com/sol3/papers....

The Sources of Researcher Variation in Economics

We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretat

papers.ssrn.com

Rachel M. Perera @rachelmarisa.bsky.social · 2y ago

this from a representative at American Institutes for Research about DOGE/Trump cancelling IES contracts is spot on (& good on them for speaking out clearly about this)

“This is an incredible waste of taxpayer dollars, which have been invested—per Congressional appropriations and many according to specific legislation—in long-standing data collection and analysis efforts, and policy and program evaluations,” Tofig said. “These investments inform the entire education system at all levels about the condition of education and the distribution of students, teachers, and resources in school districts across America. Many of these contracts are nearing completion and canceling them now yields the taxpayers no return on their investment. If the purpose of such cuts is to make sure taxpayer dollars are not wasted and used well, the evaluation and data work that has been terminated is exactly the work that determines which programs are effective uses of federal dollars, and which are not.”

Katherine Knott@knottkatherine.bsky.social · 2y ago