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.

This one is on-line now: . (journals.sagepub.com/home/cpx). It's a response to commentaries on our paper documenting the inadequacy of Open Science training in Clinical PhD programs in the US. See post below for a synopsis and links to open access versons of our original paper and response.

Clinical Psychological Science: Sage Journals

journals.sagepub.com

Don Lynam@drlynam.bsky.social · 5mo 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

⚠️ATTENTION STRESS GENERATION FANS!⚠️ Presenting THREE new papers in Nature Reviews Psychology and Journal of Psychopathology and Clinical Science! One empirical study One methods guide One conceptual framework All have been baking for a LONG time, so it is a thrill to finally share. 🔗🧵⬇️ #PsychSky

I was excited to be a part of this project, but disappointed by what we found. Antagonistic forms of psychopathology (ASB, aggression, psychopathy, narcissism, etc) are grossly underfunded compared to other spectra. This is especially unfortunate given the impact on society. 1/2

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

Extremely excited to (briefly) discuss a new Registered Report led by @nphillips36.bsky.social in press at J. of Psychopathology and Clinical Science. We used LLMs to code over 53,000 grant abstracts from 2020 to 2024; all were funded by NIMH, NIDA, NIAAA, NIHCD.

Super excited to share a thread on our recent paper, “Mapping United States federal funding for mental health difficulties from 2020-2024 to the Hierarchical Taxonomy of Psychopathology: A registered report,” now in press at Journal of Psychopathology and Clinical Science! osf.io/preprints/ps... 🧵

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Thrilled to share our registered report at Journal of Psychopathology and Clinical Science! In it, we mapped all funding from NIMH, NIDA, NIAAA, and NICHD from 2020-2024 according to HiTOP (@hitop-system.bsky.social) osf.io/preprints/ps...

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osf.io

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

Extremely excited to (briefly) discuss a new Registered Report led by @nphillips36.bsky.social in press at J. of Psychopathology and Clinical Science. We used LLMs to code over 53,000 grant abstracts from 2020 to 2024; all were funded by NIMH, NIDA, NIAAA, NIHCD.

Anybody know of good applied examples of dyadic response surface analysis with repeated measures? Preference would be in the context of intensive longitudinal data but would appreciate any and all recs using this approach (especially ones that have open code!) #StatsSky #rstats

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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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.

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 · 3mo 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?

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 · 3mo ago

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

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 · 3mo ago

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...

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 · 5mo 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

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 · 5mo 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…