Daniel P. Moriarity
@dpmoriarity.bsky.social
5.1K followers 1.9K following 2.9K posts
Assistant Professor of Clinical Psychology @ UPenn | Quant-curious | Lv. 11 Dwarf paladin Inflammatory phenotyping, physiometrics, precision psychiatry Statistics, Transparency, + Rigor Editor @ Psychological Science
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dpmoriarity.bsky.social
First paper from my lab @upenn.edu (open access) @ Biological Psychiatry w/ @emilyrperkins.bsky.social [email protected]

We discuss the need to falsify theories of biology predicting syndromes vs. syndromes in ways that allow both to be true 🧵1/10

authors.elsevier.com/sd/article/S...
dpmoriarity.bsky.social
of course, thanks for helping me dig through!
dpmoriarity.bsky.social
you for your help!

FWIW (still some digging to do), I think it has something to do w/ consecutive assessments per person. I thought specifying ID but per bsky.app/profile/mans... was enough but when I specify start + end time the curve the "at risk" corrects to be N (right) instead of obvs (left)
Reposted by Daniel P. Moriarity
russpoldrack.org
OpenNeuro @openneuro.bsky.social just hit a huge milestone: 1500 datasets! Congrats to the team on making this project so successful over the last 7 years.
Reposted by Daniel P. Moriarity
drlynam.bsky.social
Exciting news from the Academy of Psychological Clinical Science--a joint effort to enhance open science training in clinical psychology!

If you are interested, you can the papers mentioned in the email here:
Van Til et al. osf.io/h34jg/files/...
OSC paper (Lynam et al.) osf.io/preprints/ps...
Reposted by Daniel P. Moriarity
jeremymberg.bsky.social
VOTE VOTE VOTE VOTE VOTE

If you have an election in your area, VOTE!
Ballot receipt email from Allegheny County
dpmoriarity.bsky.social
interesting, thank you so much! If my following of the documentation is correct, does this automatically transition this to an interval censored scheme, or is right censoring still the right fit?

I think (?) right censored is most appropriate. RQ is on time-to-remission in treatment
dpmoriarity.bsky.social
thanks, Libby! Sorry for misunderstanding, incorrectly assumed that the graph was to identify the 50% threshold of whether the event happened

Pulled up the figure and it never crosses .5, which odd. Seems that it isn't determining median relating to # of people, its using # of observations...
dpmoriarity.bsky.social
eh, as I'm digging in a bit more I don't think interval censoring is feasible since the assessments are still day of vs "did the event happen between now and your last assessment"
dpmoriarity.bsky.social
I double checked the coding and came up with some observations that underscored I think I'm misunderstanding something fundamental. Also had the thought that maybe interval censoring is more appropriate here since we only do assessments every ~2 weeks bsky.app/profile/dpmo...
dpmoriarity.bsky.social
I do have consecutive time periods for each individual, but I'm seeing two things during some diagnostics that are making me thing I misunderstood how to structure my data or communicate to the command what the data structure is 1/3
dpmoriarity.bsky.social
Since this is right-censored, my understanding was that time points before the event should be 0, the event should be 1, then observations after the event should be missing but, when I run just the surv(), it is labeling the "0"s as censored yellow highlights = same ID across pics) 2/2
dpmoriarity.bsky.social
I do have consecutive time periods for each individual, but I'm seeing two things during some diagnostics that are making me thing I misunderstood how to structure my data or communicate to the command what the data structure is 1/3
dpmoriarity.bsky.social
Thanks, Frank! Im trying to focus on the median here, it seems from the N and Events columns that this should have reached the 50% threshold, unless I'm misunderstanding something (probably am at this point)
dpmoriarity.bsky.social
good point, attached for more info, thanks! All time points after the event are missing, event =1, pre-event =0.

Going to check into the logical coding when I get back to the computer...that might be the lead!
dpmoriarity.bsky.social
I didn't think so? But maybe I set up the coding wrong. There are multiple observations per individual, but any time point prior to the event is labeled as "0" and when the event happens they are labeled as "1", but I'm gathering from your response this set-up is incorrect...
dpmoriarity.bsky.social
Correct, it's a Cox regression from using survfit(surv()) but no covariates in this model. And only 1 event per person!
dpmoriarity.bsky.social
I interpreted this to mean if the event happened on > 50% of the sample , which it did. Or are you referring to some other property?
dpmoriarity.bsky.social
That would have been good info to include...

Survival package, survfit function
dpmoriarity.bsky.social
Cannot for the life of me find a relevant post on CrossValidated so internet please help.

Running a survival analysis where >50% of the sample had the event, but it isn't able to calculate the median or confidence interval. Never seen this one before... Any explanations?

#Rstats
Reposted by Daniel P. Moriarity
Reposted by Daniel P. Moriarity
olivia.science
New preprint 🌟 Psychology is core to cognitive science, and so it is vital we preserve it from harmful frames. @irisvanrooij.bsky.social & I use our psych and computer science expertise to analyse and craft:

Critical Artificial Intelligence Literacy for Psychologists. doi.org/10.31234/osf...

🧵 1/
Cover page of Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 1 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1 Table 2 Guest, O., & van Rooij, I. (2025, October 4). Critical Artificial Intelligence Literacy for Psychologists. https://doi.org/10.31234/osf.io/dkrgj_v1
Reposted by Daniel P. Moriarity
richraho.bsky.social
Chicago priest Fr. Larry Dowling describes procession to ICE facility: “No one had the courage to speak directly to us. No one from Homeland Security could stand in the presence of the Monstrance holding the Blessed Sacrament. No wonder. Evil is repelled, recoils in the presence of Christ.”
Reposted by Daniel P. Moriarity
markhisted.org
Seeing a lot of celebration of this as a win.

But at NIH we have seen this exact play before.

It looks like it is the Vought strategy -and to stop the lawless firings we have to see the bigger picture.
A 🧵:
Trump Administration Will Rehire Scores of Experts Fired in Error
www.nytimes.com
Reposted by Daniel P. Moriarity
markhisted.org
Looks from here like the goal is to create confusion, and focus public attention on a subset of the most outrageous firings — to distract from the other firings.

We shouldn’t be fooled, and should demand that all the illegal shutdown RIFs are made null and void. /end