Tiffany Wu
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tiffanyxwu.bsky.social
Tiffany Wu
@tiffanyxwu.bsky.social
820 followers 510 following 15 posts
Edpsych PhD & Stats dual master's @UMich | IES Predoc Fellow | #rstats enthusiast | Former teacher | @NorthwesternU & @UChicago alumna | 🇹🇼🇺🇸

Website: https://tiffany-wu.github.io/
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tiffanyxwu.bsky.social
Tiffany Wu @tiffanyxwu.bsky.social · Nov 15
Hello new friends! 👋 I’m Tiffany. I’m a PhD candidate at UMich interested in edpsych 🧠, early childhood 🎒, and machine learning 🖥️. I make pretty pictures using #rstats once in a while (👇). Looking forward to (re)building community & learning from + with y'all! #EduSky #introduction
Reposted by Tiffany Wu
paul-bruno.com
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
September 22, 2025 at 10:59 AM
Reposted by Tiffany Wu
aaronsojourner.org
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/...
March 12, 2025 at 1:29 AM
Reposted by Tiffany Wu
doughesm.bsky.social
🚨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...
www.bc.edu
August 29, 2025 at 2:41 PM
Reposted by Tiffany Wu
annenberginstitute.bsky.social
📢 #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
August 25, 2025 at 1:03 PM
Reposted by Tiffany Wu
joshua-goodman.com
🔥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?
June 25, 2025 at 12:50 PM
Reposted by Tiffany Wu
paul-bruno.com
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
www.paul-bruno.com
June 16, 2025 at 10:31 AM
Reposted by Tiffany Wu
joshua-goodman.com
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
June 11, 2025 at 4:41 PM
tiffanyxwu.bsky.social
🤔 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.
May 28, 2025 at 1:08 PM
Reposted by Tiffany Wu
annenberginstitute.bsky.social
🚀 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
May 27, 2025 at 2:01 PM
Reposted by Tiffany Wu
weilanch.bsky.social
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!)
annenberginstitute.bsky.social Annenberg Institute @annenberginstitute.bsky.social · May 22
📢 #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
May 22, 2025 at 4:00 PM
Reposted by Tiffany Wu
johnholbein1.bsky.social
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.
May 12, 2025 at 2:57 PM
Reposted by Tiffany Wu
andrew.heiss.phd
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")
April 18, 2025 at 6:19 PM
Reposted by Tiffany Wu
chloergibbs.bsky.social
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...
April 18, 2025 at 7:45 PM
Reposted by Tiffany Wu
vincentab.bsky.social
📚😅🎉

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
April 10, 2025 at 7:06 PM
Reposted by Tiffany Wu
andrew.heiss.phd
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
March 20, 2025 at 6:30 PM
Reposted by Tiffany Wu
dynarski.bsky.social
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
andrewdeanho.bsky.social Andrew Ho @andrewdeanho.bsky.social · Mar 14
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.
aeraedresearch.bsky.social AERA @aeraedresearch.bsky.social · Mar 14
AERA has just learned that all restricted-use NCES data licenses will be cancelled, possibly as early as March 20. We urgently request that all AERA members and others in the research community with restricted-use licenses take these two actions: www.aera.net/Research-Pol...
March 15, 2025 at 12:21 AM
Reposted by Tiffany Wu
carajackson.bsky.social
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
March 12, 2025 at 4:46 PM
Reposted by Tiffany Wu
andrew.heiss.phd
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
March 12, 2025 at 5:36 PM
Reposted by Tiffany Wu
bethschueler.bsky.social
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
March 5, 2025 at 8:43 PM
Reposted by Tiffany Wu
nickchk.com
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
February 25, 2025 at 7:17 PM
Reposted by Tiffany Wu
rachelmarisa.bsky.social
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.”
February 11, 2025 at 1:41 AM
Reposted by Tiffany Wu
ericahgreenberg.bsky.social
🌟 Did you know that most federal education data are archived in the @urbaninstitute.bsky.social Education Data Explorer? It's a great resource for research and analysis - and there's even a full API version linked in thread. 🌟

#EduSky #EdPoliSky #EduSkyECEC
educationdata.urban.org/data-explorer
Education Data Explorer
Explore education data
educationdata.urban.org
February 10, 2025 at 9:19 PM
Reposted by Tiffany Wu
lucystats.bsky.social
a bit more #Severance data
please enjoy all analyses equally

👉 lucymcgowan.github.io/mdr-website/

and for my #rstats friends:
👉 lucymcgowan.github.io/mdr/
January 31, 2025 at 2:54 PM
tiffanyxwu.bsky.social
"Data is carved out of the world, by someone, for some purpose, with some limits."
January 23, 2025 at 1:08 AM
Reposted by Tiffany Wu
jinxungoh.bsky.social
If you/ your students are interviewing for PhD psych programs in US (especially social psych), check out the resource page on my website. There are guides prepped by grad students + questions to ask faculty etc. Good luck!
www.pbandjlab.com/resources
The PB&J Lab - Resources
Resources
www.pbandjlab.com
January 18, 2025 at 5:22 PM