Greg Depow

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UNC is hiring in Quantitative Psychology! Assistant Professor (tenure-track). Please share widely! Find details here: unc.peopleadmin.com/postings/307...

It depends: Logistic is for binary variables typically coded as 0 or 1, e.g., disease or not. Poisson is for count variables, e.g. number of drinks per week. For poisson, people use Incidence Rate Ratios instead of Odds Ratios, but both can be converted to statements about Quantities of Interest.

Transformation starts at the periphery of networks where pushback is less - Scientific Reports Scientific Reports - Transformation starts at the periphery of networks where pushback is less

Intervening on a central node in a network likely does little given that its connected neighbors will "flip it back" immediately. Happy to see this position supported now.

"Change is most likely [..] if it spreads first among relatively poorly connected nodes."

www.nature.com/articles/s41...

Good explanation of odds ratios. As Noah notes, ORs can often be tough to interpret. One way to improve interpretability is to present results in terms of Quantities of Interest such as probabilities (logistic) and counts (poisson/negative binomial) as argued here: psycnet.apa.org/doiLanding?d...

Thinking about odds ratios...

An odds is a ratio of events to non-events. For example, if the event is survival, the odds of survival is the number of survivors per death. If the event is getting a disease, the odds is the number of diseased individuals per healthy individual.

Making sense of some odd ratios: A tutorial and improvements to present practices in reporting and visualizing quantities of interest for binary and count outcome models Generalized linear models (GLMs) such as logistic and Poisson regression are among the most common statistical methods for modeling binary and count outcomes. Though single-coefficient tests (odds rat...

Halvorson et al. (2021) should probably be required reading for folks working with binary and count data (@kevinmking.bsky.social )

pmc.ncbi.nlm.nih.gov/articles/PMC...

Final week to apply for the 2026 SFI Complexity Postdoctoral Fellowships

If you're an early-career scholar and passionate about collaborative, transdisciplinary research beyond traditional departments, this is the postdoc fellowship for you.

Deadline: Oct 1, 2025

Apply: santafe.edu/sfifellowship

🚨 Spread the word! We're (w/ @whitneyringwald.bsky.social & @aleksakaurin.bsky.social) organizing a special issue at PD:TRT focused on innovations for measuring context in ambulatory assessment studies of personality pathology. We'd love for you (yes, you) to submit a proposal (deadline Nov. 14th):

Whoa—my book is up for pre-order!

𝐌𝐨𝐝𝐞𝐥 𝐭𝐨 𝐌𝐞𝐚𝐧𝐢𝐧𝐠: 𝐇𝐨𝐰 𝐭𝐨 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭 𝐒𝐭𝐚𝐭 & 𝐌𝐋 𝐌𝐨𝐝𝐞𝐥𝐬 𝐢𝐧 #Rstats 𝐚𝐧𝐝 #PyData

The book presents an ultra-simple and powerful workflow to make sense of ± any model you fit

The web version will stay free forever and my proceeds go to charity.

tinyurl.com/4fk56fc8

Pseudo Effects: How Method Biases Can Produce Spurious Findings About Close Relationships - Samantha Joel, John K. Sakaluk, James J. Kim, Devinder Khera, Helena Yuchen Qin, Sarah C. E. Stanton, 2025 Research on interpersonal relationships frequently relies on accurate self-reporting across various relationship facets (e.g., conflict, trust, appreciation). Y...

In a new paper, my colleagues and I set out to demonstrate how method biases can create spurious findings in relationship science, by using a seemingly meaningless scale (e.g., "My relationship has very good Saturn") to predict relationship outcomes. journals.sagepub.com/doi/10.1177/...

🚨We're hiring!🚨 The Dept of Psychology at Rutgers is hiring an Assistant Professor in Social Psychology. Review of applications begin on Oct 18. Details here: jobs.rutgers.edu/postings/259...

I'm chairing the search committee and am happy to field questions about the position. 🧵

Assistant Professor of Psychology - Madison, Wisconsin, United States Current Employees: If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.Job Category:FacultyEmployment Type:Regula...

The Dept. of Psychology at the U. Wisconsin–Madison has an opening for an Assistant Professor in the area of Computational Neuroscience and/or Cognitive Science, with an emphasis on artificial intelligence (AI).

Domain of behavior or cognition is open. Details at jobs.wisc.edu/jobs/assista...

For our scientists.

By @ellecordova.bsky.social

Haha 🤣
Fair enough

Get a session manager extension for your browser. You can categorize and save your tabs and open them on your new laptop!

I'm happy to announce that Vanderbilt Psychology's clinical area is hiring a TT asst prof this year! Please share with your networks and consider applying if you're on the market! Happy to (try to) answer questions about the search if you have them.

Link here: apply.interfolio.com/173316

Come be my colleague! The Department of Psychology at Princeton and @princetonneuro.bsky.social‬ are jointly searching for an Assistant Prof in Cog Neuro. puwebp.princeton.edu/AcadHire/app...

We're hiring TWO social psychologists (one health, one any area of social) at U of Utah! Pls share widely, and reach out if you have any questions! utah.peopleadmin.com/postings/186...

New Open dataset alert:
🧠 Introducing "Spacetop" – a massive multimodal fMRI dataset that bridges naturalistic and experimental neuroscience!

N = 101 x 6 hours each = 606 functional iso-hours combining movies, pain, faces, theory-of-mind and other cognitive tasks!

🧵below

Assistant Professor in Psychology Position Title: Assistant Professor in Psychology Appointment Type: Faculty Job Description: Summary of Duties and Responsibilities: The Department of Psychology in the College of Liberal Arts and Sci...

Come and work with me in beautiful Ames!
isu.wd1.myworkdayjobs.com/en-US/IowaSt...

Thank you, Brett! 🥳

Thank you, Kaitlyn!! 🙌

Exciting news! I'll be working with the Center for Digital Thriving @digitalthriving.bsky.social as a fellow to develop an intervention aimed at improving the well-being of youth on social media. The intervention will train youth to engage skilfully with emotions on their feed using wise empathy.

We are HIRING! The Department of Psychology at NDSU is seeking a tenure-track Assistant Professor in Developmental Psychology (broadly defined) to begin August, 2026. Full details here: tinyurl.com/3sjknmxn
Questions can be directed to me.
Please share widely!

#psychjobs

Same energy
xkcd.com/552/

If you are preparing your bachelor statistics course and would like to add optional material for students to better understand statistics on a conceptual level (see topics in the screenshot) my free textbook provides a state of the art overview. lakens.github.io/statistical_...

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.

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...

Our department is hiring!
Tenure-track, OPEN RANK, social psychologist.

Looking for someone loves undergrad teaching but also has or wants to build a serious research program.

Good space, startup, caring department.

?s re: department/school/location? DM me.

#psychscisky
#socialpsyc
#psychjobs

🥳🥳🥳