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Nate Phillips

@nphillips36.bsky.social

Clinical Psych PhD student at the University of Georgia. Incoming clinical intern at the Charleston Consortium/MUSC. Interested in personality, externalizing psychopathology, open science, and methods.

147 Posts1408 Follower814 Folgt
Nadine Batchelor-Hunt@nadinebh.bsky.social · 6d ago

This statement by UEFA on FIFA attempting to sell off the World Cup gave me goosebumps, what a statement - the beautiful game deserves no less “As so long as Europe has a voice, it will never be for sale.”

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Ted Schwaba@tedmond.bsky.social · 3w ago

New meta by @peterhaehner.bsky.social et al (I'm a little middle author) on individual differences in personality change across the lifespan (229 studies, N = 230k) 10.1037/bul0000525 Cool finding (imo): For all Big Five, variance in change is greatest in youth, declining through young adulthood!

Individual differences in change for each of the Big Five across ages 0 to 80. The trend for each trait is that individual differences in change are decreasing with age.
Don Lynam@drlynam.bsky.social · 3w ago

New paper (open access) from M. Packer West, Vera Du, @kaelavantil.bsky.social, @jdmiller.bsky.social, and me. We used the TPM model to organize a meta-analysis on the relation between psychopathy and sexual agression (117 samples, > 41,000 participants). 1/2 onlinelibrary.wiley.com/doi/10.1111/...

The Relation Between Psychopathy and Sexual Aggression: A Meta‐Analysis

Objective Psychopathy is a multifaceted, hierarchical construct that has been linked to aggression and antisocial behavior. The triarchic model of psychopathy comprises three underlying, distinct tr...

onlinelibrary.wiley.com

Courtland Hyatt@courtlandhyatt.bsky.social · 3w ago

Super proud to be a part of this Registered Report, led by the stellar @nphillips36.bsky.social. It’s got it all - cool/interesting/important research question, alignment w/open science principles, clinical relevance, comprehensive sensitivity analyses, and so on. Give it a read!

Nate Phillips@nphillips36.bsky.social · 3w ago

Very excited to share this registered report now in press at Clinical Psych Science! In this paper, we put a common clinical intuition in group-based treatment to the test: Are patients’ outcomes associated with the personality composition of their treatment cohort?

Nate Phillips@nphillips36.bsky.social · 3w ago

Very excited to share this registered report now in press at Clinical Psych Science! In this paper, we put a common clinical intuition in group-based treatment to the test: Are patients’ outcomes associated with the personality composition of their treatment cohort?

PsyArXivBot@psyarxivbot.bsky.social · 4w ago

Cohort Personality Composition’s Prediction of Treatment Outcomes in a Military Intensive Outpatient Program: A Registered Report: https://osf.io/xgr8w

Nate Phillips@nphillips36.bsky.social · last mo.

Awesome to see this out! We argue that the main implication of Kerber et al. (2026) is that self-reported personality functioning and depression are practically fungible Also, big shoutout to Kerber and co. for making their data publicly available and being friendly/helpful throughout the process!

Josh Miller@jdmiller.bsky.social · last mo.

Excited to share a new commentary set to be published in J. of Psychopathology and Clinical Science. Co-authored with @vizecolin.bsky.social (shared 1st), @nphillips36.bsky.social, and @drlynam.bsky.social. osf.io/preprints/ps...

Brian Nosek@briannosek.bsky.social · 3mo ago

Wonderful commentary about open science culture change situating the responsibility in ourselves to change the system, not wait for some imagined entity to come change it for us.

Don Lynam@drlynam.bsky.social · 3mo ago

Excited to share this one: Open Science Now: A Response to Commentaries on Van Til et al. (with @kaelavantil.bsky.social, @nphillips36.bsky.social, Tinawei (Vera) Du, Leigha Rose, @jdmiller.bsky) osf.io/preprints/ps... See below for the TLDR version 1/8

Aidan Wright@aidangcw.bsky.social · 3mo ago

Lot's of folks cheering this paper's implications, as if it shows all's well in how we do science and can return to business as usual. IT DOES NOT SAY THAT! But by the paper's own logic, if we can't establish a crisis (using binary replication rates), we also can't say there isn't a crisis. 1/3

Berna Devezer@devezer.bsky.social · 3mo ago

📣 The difference between replicable and not replicable is not itself scientifically replicable. 📣 New work with Erkan Buzbas, showing that verdicts such as "X% of results replicated" are based on an inferential machinery that doesn't work. arxiv.org/abs/2604.26268

Screenshot of a paper's title page. Title: "The Difference Between 'Replicable' and 'Not replicable' is not Itself Scientifically Replicable". Authors: Berna Devezer and Erkan O. Buzbas, both at the University of Idaho — Devezer in the Department of Business and the Institute for Modeling Collaboration and Innovation, Buzbas in the Department of Mathematics and Statistical Science. Authors contributed equally. Corresponding author: bdevezer@uidaho.edu. Abstract: Replication studies estimate the replicability rate of scientific results by aggregating binary verdicts of experiments. Exact replications are rarely attainable, so most replication sequences are non-exact. Experiments differ in ways that matter and do not share a single common data-generating process. We formalize two statistical interpretations of this non-exactness. In a shared latent rate model (benchmark), experiments are exchangeable and depend on a common random replicability rate. In a conditionally independent rates model (operational), each experiment has its own replicability rate drawn independently from a population distribution. Under the shared latent rate model, even small variability among replicability rates induces an irreducible variance floor on the estimated mean replicability rate that cannot be eliminated by adding more replications. Under the conditionally independent rates model, the degree of non-exactness is not identifiable from standard replication data, because one binary verdict per experiment contains no information about between-experiment heterogeneity. Researchers therefore cannot tell which precision regime they are operating in or whether high- and low-replicability sequences can be distinguished in principle. As a result, the usual data structure of one binary verdict per experiment cannot support reliable demarcation between "replicable" and "not replicable" results and systematically understates uncertainty, making high- and low-replicability sequences appear discrim…
Nate Phillips@nphillips36.bsky.social · 5mo ago

Happy to see this now out at JRP For this one, we took a swing at integrating two historically siloed literatures that focus on the individual differences related to externalizing behaviors: personality and formidability

Dillon Wong@dillonmwong.bsky.social · 5mo ago

Excited to share our new paper, “Testing the additive and interactive relations of personality and physical indicators of formidability with externalizing behaviors,” now accepted at Journal of Research in Personality! doi.org/10.1016/j.jr...

Richard McElreath 🐈‍⬛@rmcelreath.bsky.social · 8mo ago

The Max Planck Society has begun an exploratory round table for open science. We are drafting some recommendations to leadership. Still a long way to go! But here are my notes on the most recent draft, just so you all know how I am trying to steer things.

Richard McElreath: It must not be overlooked that junior researchers DO NOT TRUST US. We, the directors, are a big part of the problem. We made this system, we remake it every year, and we benefit from it. What can we do to credibly signal our commitment to reform a corrupt research culture? My conversations with junior scientists in the society has taught me that directors are too often either indifferent or hostile to science reform. We cannot hope to convince our prize winning colleagues. Their egos are immune. But we can replace retirements with researchers who care more about integrity than their own prestige. This is important both for earning the trust of the junior researchers who really do the research in the MPG and for attracting excellent future directors and starting to earn the trust of the public. So I suggest two strong signals to our junior researchers (and the public): (1) we will reform recruitment and promotion at all levels to eliminate proxies like citation counts and journal brands in favor of reliability and sustainability; (2) we will make open science skills a core part of scientific training, through the graduate schools at a minimum, as conditions for the central funding. The most ambitious thing we could do, as hinted at in item 5 above, is to meaningfully invest in metascientific research. As the largest basic research organization in the world, the MPG is uniquely suited to studying research and its products from a broad perspective that includes the humanities, the sciences, and policy. Governments are already involved in science reform. Someone should study it in an organized and sustained way.
Josh Miller@jdmiller.bsky.social · 8mo ago

Excited to share a Registered Report in J. of Personality looking at the “perils of partialing” – led by the Bluesky-less Leigha Rose with @drlynam.bsky.social and me. (1) onlinelibrary.wiley.com/doi/10.1111/...

Perils of Partialing: Can Scholars Predict Residualized Variables' Nomological Nets?

Objective Partialing is a statistical procedure in which the variance shared among two or more constructs is removed, allowing researchers to examine the unique properties of the residualized, parti...

onlinelibrary.wiley.com

Raphael Merz@raphaelmerz.bsky.social · 9mo ago

Very useful table of insufficient examples vs. best-practices for statistical reporting! Will definitely point some of my colleagues to it! 📈

Table with insufficient examples vs. best-practice for things like reporting hypotheses, null results, or the software you used. See https://doi.org/10.1038/s44271-025-00356-w for the full table.
Dan Quintana@dsquintana.bsky.social · 9mo ago

Our paper on improving statistical reporting in psychology is now online 🎉 As a part of this paper, we also created the Transparent Statistical Reporting in Psychology checklist, which researchers can use to improve their statistical reporting practices www.nature.com/articles/s44...

Transparent and comprehensive statistical reporting is critical for ensuring the credibility, reproducibility, and interpretability of psychological research. This paper offers a structured set of guidelines for reporting statistical analyses in quantitative psychology, emphasizing clarity at both the planning and results stages. Drawing on established recommendations and emerging best practices, we outline key decisions related to hypothesis formulation, sample size justification, preregistration, outlier and missing data handling, statistical model specification, and the interpretation of inferential outcomes. We address considerations across frequentist and Bayesian frameworks and fixed as well as sequential research designs, including guidance on effect size reporting, equivalence testing, and the appropriate treatment of null results. To facilitate implementation of these recommendations, we provide the Transparent Statistical Reporting in Psychology (TSRP) Checklist that researchers can use to systematically evaluate and improve their statistical reporting practices (https://osf.io/t2zpq/). In addition, we provide a curated list of freely available tools, packages, and functions that researchers can use to implement transparent reporting practices in their own analyses to bridge the gap between theory and practice. To illustrate the practical application of these principles, we provide a side-by-side comparison of insufficient versus best-practice reporting using a hypothetical cognitive psychology study. By adopting transparent reporting standards, researchers can improve the robustness of individual studies and facilitate cumulative scientific progress through more reliable meta-analyses and research syntheses.
Nate Phillips@nphillips36.bsky.social · 9mo ago

Massive and important undertaking by @andrew-cast.bsky.social, @drlynam.bsky.social, and co in estimating when interaction effects stabilize in linear regression Tldr: Under realistic conditions for psych research, N = 3,800

Don Lynam@drlynam.bsky.social · 9mo ago

Another paper in our effort to get folks to stop routinely testing interactions. This time from the angle of stability. Led by @andrew-cast.bsky.social with help from @vizecolin.bsky.social, @jdmiller.bsky.social, @davidbaranger.bsky.social, and me. Forthcoming in AMPPS. osf.io/preprints/ps... 1/8

Don Lynam@drlynam.bsky.social · 10mo ago

Interactions are difficult to detect in field studies as they are typically tiny--very small to start with and made smaller by the joint unreliabilities of the components. Here, we find some but the contribution to explained variance is negligible. Call off the search. It is not worth the effort.

David Baranger@davidbaranger.bsky.social · 11mo ago

𝐀𝐝𝐝𝐢𝐭𝐢𝐯𝐞 𝐚𝐧𝐝 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐨𝐟 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐂𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧 𝐖𝐢𝐭𝐡𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥𝐢𝐳𝐢𝐧𝐠 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐬 | "Although interaction effects were detected, they were small and practically negligible in their explanation of variance in externalizing behaviors" journals.sagepub.com/doi/10.1177/...