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Posts by Siwei Liu

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The NSF 2027 budget has noted that they will close out the Social, Behavioral, and Economic Science Program (SBE). This is not a good thing. nsf-gov-resources.nsf.gov/files/FY-202...

2 weeks ago 550 396 22 93

Have examples of social science papers that use DAGs to justify their controls? I find these very hard to come by & would like to use for teaching.

1 month ago 9 3 3 2
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Research Associate in Psychology in Charlottesville, Virginia, United States of America | Research at University of Virginia Apply for Research Associate in Psychology job with University of Virginia in Charlottesville, Virginia, United States of America. Research at University of Virginia

Hello all! I’m recruiting a postdoc to work with my lab and I on methods for analyzing intensive longitudinal timeseries of psychological phenomena, with particular focus on measurement and optimization of interventions! Start would be August 2026

3 months ago 5 2 0 0

📢 Call for Papers:
We’re excited to announce an upcoming Psychometrika Special Issue on Data Intensive Methods in Psychometrics (think of using many datasets for methodological development), guest edited by @klint.bsky.social, @kyliegorney.bsky.social, @jmbh.bsky.social, Ben Domingue, and me.

3 months ago 5 5 0 0

Which is why assumptions you can check aren't very helpful: if an assumption doesn't cost anything it won't buy much

3 months ago 20 6 2 3
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WARN-D machine learning competition is live » Eiko Fried If you share one single thing of our team in 2026—on social media or per email with your colleagues—please let it be this machine learning competition. It was half a decade of work to get here, especi...

After 5 years of data collection, our WARN-D machine learning competition to forecast depression onset is now LIVE! We hope many of you will participate—we have incredibly rich data.

If you share a single thing of my lab this year, please make it this competition.

eiko-fried.com/warn-d-machi...

3 months ago 189 159 5 7

Call for papers: Emotion special issue on Affect Dynamics Across Multiple Timescales (moments→days→years) and links to mental and physical health. Letters of intent due Jan 15, 2026. Details/submission:

www.apa.org/pubs/journal...

Please share with colleagues/trainees. @affectscience.bsky.social

4 months ago 21 18 0 3
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Number of ‘unsafe’ publications by psychologist Hans Eysenck could be ‘high and far reaching’ Hans Eysenck A “high and far reaching” number of papers and books by Hans Eysenck could be “unsafe,” according to an updated statement from King’s College London, where the psychologist was a profe…

Diederik Stapel was a massive watershed moment in psychology.

However, he was -- and let's be slightly glib here -- some guy from The Netherlands who wrote social psychology papers.

The full accounting of the Eysenck case is approx, at minimum, TWO STAPELS.

retractionwatch.com/2025/12/03/n...

4 months ago 109 68 4 22

Come work with us @unm.edu 🤩

5 months ago 9 9 0 0
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Postdoctoral Fellow - Large Language Models as Models for Human Development This position is part of the Post Doctoral Fellows Association and has an initial appointment of two years. This position has a comprehensive benefits package. Location - This role is in-person at Nor...

I'm hiring (another) post doc, this time in collaboration with Natalie Brito @nataliebrito.bsky.social at Columbia! We will be exploring some of the characteristics of human development using deep learning models. Email with questions!
iaejup.fa.ocs.oraclecloud.com/hcmUI/Candid...

5 months ago 8 4 0 1
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New job ad: Assistant Professor of Quantitative Social Science, Dartmouth College apply.interfolio.com/172357

Please share with your networks. I am the search chair and happy to answer questions!

8 months ago 178 168 2 8

Interesting new special issue in Psychological Assessment.

Edited by Kristin Naragon-Gainey and @kstanton.bsky.social

Here's their overview paper: psycnet.apa.org/record/2026-...

And here's our contribution, which will win us no friends:
psycnet.apa.org/record/2026-...

5 months ago 41 16 2 2

Happy to share that our large-scale network analysis is now out in @nathumbehav.nature.com

We show that networks are often supported by too little evidence from the data for results to be reported with confidence, not meaning that results are flawed but rather suggests caution in interpretation.

6 months ago 7 3 0 0

Great study! A general implication is that when we infer effects of retrospectively measure variables on outcomes, we’re largely just seeing the effects of how people are currently feeling.

6 months ago 29 9 1 0

Wow, congrats!

7 months ago 1 0 0 0
Rethinking measurement invariance causally

Highlights:
It is preferable to work with a causal definition of measurement invariance
A violation of measurement invariance is a potentially substantively interesting observation
Standard tests for measurement invariance rely on strong assumptions
Group differences can be thought of as descriptive results

Rethinking measurement invariance causally Highlights: It is preferable to work with a causal definition of measurement invariance A violation of measurement invariance is a potentially substantively interesting observation Standard tests for measurement invariance rely on strong assumptions Group differences can be thought of as descriptive results

Conceptual graph illustration the central points of the manuscript. A group variable is potentiall connected to a construct of interest which affects items. Measurement invariance is violated if the group variable directly affects the items, for example by modifying the loadings from the construct to the items, or by directly affecting an item

Conceptual graph illustration the central points of the manuscript. A group variable is potentiall connected to a construct of interest which affects items. Measurement invariance is violated if the group variable directly affects the items, for example by modifying the loadings from the construct to the items, or by directly affecting an item

To make this less abstract, consider a scenario where students take an exam, R, meant to capture some ability, T, and then are admitted to a program, V, depending on their exam results: R → V. This is sufficient to result in a violation of the statistical definition of measurement invariance. Exam results and admission are not independent given ability because exam results have a direct effect on admission. Even if we know somebody’s ability (e.g., we know it’s very high), learning about their admission status (e.g., they were not admitted) can tell us something about their exam result (e.g., it may have been worse than expected). According to the causal definition, this in itself does not constitute measurement bias, which seems a sensible conclusion here. After all, the scenario does not involve any reason to believe that the measurement process varied systematically by admission status. Admission happens after the exams took place, it cannot retroactively influence the measurement process (and, for example, lead to unfair treatment depending on admission status).

To make this less abstract, consider a scenario where students take an exam, R, meant to capture some ability, T, and then are admitted to a program, V, depending on their exam results: R → V. This is sufficient to result in a violation of the statistical definition of measurement invariance. Exam results and admission are not independent given ability because exam results have a direct effect on admission. Even if we know somebody’s ability (e.g., we know it’s very high), learning about their admission status (e.g., they were not admitted) can tell us something about their exam result (e.g., it may have been worse than expected). According to the causal definition, this in itself does not constitute measurement bias, which seems a sensible conclusion here. After all, the scenario does not involve any reason to believe that the measurement process varied systematically by admission status. Admission happens after the exams took place, it cannot retroactively influence the measurement process (and, for example, lead to unfair treatment depending on admission status).

New paper out with @boryslaw.bsky.social 🥳 In which we sketch out how to rethink measurement invariance causally for applied researchers. And provide a causal definition of measurement invariance!

www.sciencedirect.com/science/arti...

7 months ago 113 36 3 1
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Assistant Professor, Psychological Sciences - Flagstaff, Arizona, United States About the Department/College The Department of Psychological Sciences is located on the Flagstaff Mountain Campus of Northern Arizona University (NAU), situated at the base of San Francisco Peaks. NAU...

Tenure-Track Quant Psyc job opening at Northern Arizona University in Flagstaff. Areas of interest are pretty broad (SEM, multilevel, or psychometrics), the deadline to apply is coming up soon (Sept 15) if you're interested!

careers.nau.edu/jobs/assista...

7 months ago 15 15 0 1
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AMPPS Call for Papers: Replicability and Reproducibility in Methodological Research. Proposals due September 15. @jkflake.bsky.social 

8 months ago 15 14 1 0

Please add me.

9 months ago 0 0 0 0

Great post! I just read this paper by @drewhalbailey.bsky.social and colleagues that shows the RI-CLPM also performs better than CLPM when there are unmeasured time-varying confounders:

psycnet.apa.org/record/2025-...

9 months ago 7 2 0 0

This work was officially accepted for publication today!

10 months ago 3 1 0 0

This is a required reading in my Intro to Research Methods class.

10 months ago 2 0 0 0

Love it!

11 months ago 1 0 1 0
Figure 1.  Trends in Biannual US Infant Mortality Rates, 2012-2023

Figure 1. Trends in Biannual US Infant Mortality Rates, 2012-2023

🧵 US states that implemented abortion bans saw higher than expected infant mortality rates, with larger increases among Black infants and those in southern states, according to this analysis of US national vital statistics data from 2012–2023.

ja.ma/4aVchPn

#MedSky

1 year ago 342 249 11 34

😭

1 year ago 0 0 0 0

Are psychometric networks sufficiently supported by data such that one can be confident when interpreting its results? We analysed 294 psychometric networks from 126 papers with the Bayesian approach to address this question @jmbh.bsky.social Sara Ruth van Holst @maartenmarsman.bsky.social 🧵

1 year ago 51 16 1 2

I don’t know if it’s an addition, but drinking too much milk tea (aka bubble tea, which is not just milk and tea but usually high in sugar) is a common problem in Chinese teenagers and a legitimate public health concern. It’s the same problem that Americans have with soda.

1 year ago 2 0 0 0
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7 steps to junk science that can achieve worldly success | Statistical Modeling, Causal Inference, and Social Science

7 steps to junk science that can achieve worldly success
statmodeling.stat.columbia.edu/2025/01/17/7...

1 year ago 30 11 0 6