Michael D. Krämer

New paper out 🎓:

Personality Traits and Provision of Grandparental Childcare: Evidence from Europe (w/ @valeriabordone.bsky.social, Giorgio Di Gessa & @mdkraemer.bsky.social

Using data from @share-eric.bsky.social, we find personality matters for grandhild care provision

doi.org/10.1080/1535...

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/...

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...

Wie verändert sich unsere Persönlichkeit über ein Jahr? Dazu starten wir heute eine neue Studie und suchen nach Teilnehmenden zwischen 18-40 Jahren, die Interesse haben, Einblicke in ihre Persönlichkeit, Wohlbefinden und Verhalten über ein Jahr zu erhalten und bis zu 173 CHF (~185€) zu verdienen.

Check out our preprint - the result of a really fun collaboration!

Updated preprint available at: osf.io/preprints/ps...

Self-improvement, self-acceptance, and/or methods effects? Travis Miller, @chopwood.bsky.social , and @wiebkeb.bsky.social, and I examined factors that might explain personality change intervention effects - now in print at JPSP 🥳: doi.org/10.1037/pspp...

Starting to look like I might not be able to work at Harvard anymore due to recent funding cuts. If you know of any open statistical consulting positions that support remote work or are NYC-based, please reach out! 😅

...with @wiebkeb.bsky.social, @chopwood.bsky.social, @peterhaehner.bsky.social, @rosalieandrae.bsky.social and Philippe Sloksnath & Lina Hungerbühler who are not on here yet 🦋

MA solitude: Call for unpublished data Meta-analysis on solitude: Call for unpublished data Dear colleagues, We are conducting a meta-analysis on personal and contextual predictors of solitude. Currently, we are looking for unpublished r...

We are conducting a meta-analysis on personal and contextual predictors of solitude. We're looking for unpublished research such as theses, unpublished manuscripts, conference submissions etc.
Full call for data: tinyurl.com/4hur45cw
Please reskeet, or message me if you know unpublished research!

Fantastic speach by @cdrosten.bsky.social on the freedom and responsibilities of researchers in these trying times

Postdoc position open in Zurich -- Prof. Martin Tomasik and I have a joint SNF project on interpretable neural network approaches for large scale, complex item / temporal structure, online learning / cognitive development data.

Please retweet.

tinyurl.com/PostdocGNNSNF

Study 1 data also available on OSF! 👀

DIW Berlin: SOEP-IS 2023 – DIPS3_DAILY: Daily Diaries and Smartphone Sensing on the Daily Level (DIPS Project)

SOEP-IS release 2023: www.diw.de/de/diw_01.c....

Amazing team 🙏, with @yannickroos.com, @ramonaschoedel.bsky.social, Mitja Back, and @drichter77.bsky.social. Without them this paper and data collection wouldn‘t have been possible. Btw, the combined experience sampling and mobile sensing data of Study 2 are now openly available as part of the

mobile sensing, affiliation motive predicted a stronger momentary social
desire and future social interactions (but only when assessed with mobile sensing). See the open-access paper for more results including on the valence and voluntariness of social interactions: doi.apa.org/doi/10.1037/...

How do people differ in pursuing their social lives? In a new paper at JPSP, lead by Cornelia Wrzus, we examined the affiliation motive (and other social traits) as moderators of how people dynamically regulate their social interactions. Across two studies with experience sampling and

Especially skills and access to software other than R are currently lacking (Stata, Mplus, hell even SPSS😅)

Interested in the computational reproducibilty of research papers? @psychscience.bsky.social Psych Science is looking to extend their network of people providing checks of reviewed manuscrips: www.psychologicalscience.org/publications...

Extremely excited to share the first effort of the Revived Genomics of Personality Consortium: A highly-powered, comprehensive GWAS of the Big Five personality traits in 1.14 million participants from 46 cohorts. www.biorxiv.org/content/10.1...

Now published at EJP: doi.org/10.1177/0890...

New preprint with @rebiweidmann.bsky.social @sophiepotter.bsky.social Dikla Segel-Karpas and Jenna Wünsche:

"When you're with me, baby, the skies will be blue for all my life? A dyadic longitudinal study of relationship happiness through midlife"

osf.io/preprints/ps...
(1/5)

🚨 Job alert - please share!

I'm looking for a doctoral researcher (3 years, 75%) to join my #ERC project #Loneliness across time and space (LOTIS) at @ruhr-uni-bochum.de, starting June 1 or later.

Details in thread 👇

#PsychSciSky

New preprint!

Ever heard that personality doesn't change? Do you believe that? (you shouldn't)

Using data from an online survey (n = 887) & eight longitudinal datasets (n = 166,971), we compared perceived vs. actual lifespan changes in personality and 20+ individual differences (1/8)
osf.io/ytmxp

SOEP, and Australian HILDA data 🇳🇱🇩🇪🇦🇺

principle of personality development. For example, those who reported to worry more, were more likely to take on informal caregiving and in turn started worrying even more as they increased their time investment. Similarly for being less lazy and more considerate! We used the Dutch LISS, German

Informal care and personality: Selection and socialization effects - Michael D. Krämer, Wiebke Bleidorn, 2025 Informal caregiving provides societally important healthcare functions but can take a toll on caregivers, with negative consequences for well-being. However, li...

Together with @wiebkeb.bsky.social I investigated how personality relates to who takes on informal caregiving, and how informal care responsibilities in turn affect personality: journals.sagepub.com/doi/10.1177/...
On the level of nuances (items), we found some evidence for the corresponsive

New Preprint Alert!

Why do people differ in their self-esteem development after a negative life event?

With M. Altorfer, and @peterhaehner.bsky.social, I addressed this question by studying self-esteem changes over six months after a negative life event.

Full preprint here: osf.io/preprints/ps...

Does smartphone use make people feel lonelier? Or does loneliness predict smartphone use?

We combined experience sampling data with smartphone usage data to examine the bidirectional association between well-being and smartphone use over time.

Published in @apajournals.bsky.social Emotion!
🧵 👇

Mein DFG Projekt läuft im Juni aus, bin also danach potentiell für Jobs zu haben. Ab jetzt freu ich mich immer wenn ihr mir was schickt, vorzugsweise Berlin aber nicht nur, möglichst Forschung. Meine Schwerpunkte sind Alters- , und Entwicklungs-, aber auch Persönlichkeits- und Arbeitspsychologie