Thiago
@csthiago.bsky.social
24 followers 71 following 34 posts
Methodologist/Epidemiologist London - UK
Posts Media Videos Starter Packs
csthiago.bsky.social
The BBC article about the paper. God... "hormone reboot"... From a survey paper....
csthiago.bsky.social
It looks that there is a problem with the statistics as well. The propensity score only uses baseline variables and treats them as time fixed. But, a second infection is a time-varying exposure. So, the "unexposed" group has been defined conditionally on the future. Right, @pwgtennant.bsky.social ?
csthiago.bsky.social
Also mediation with counts
csthiago.bsky.social
Help!
Where can I find resources about causal mediation of ordinal outcomes? (using SEM)

Thanks 😄
#rstats @dingdingpeng.the100.ci
csthiago.bsky.social
Updates about it. The CIs are likelihood ratios CIs, which can be very asymmetrical.
About the cumulative incidence, they have reinforced me that the all lower exposure curves initiate before the higher doses one.
(I still feel a bit uneasy with almost all low CIs being 1)
Reposted by Thiago
fllaha.bsky.social
I’ve had the same impression while looking at academic epidemiology postdoc offers. So much focus on AI, machine learning, LLM experience. Are these the core skills we need now? What about subject matter knowledge, study design, bias, statistics, population health knowledge? Outdated?
epilorenzofabbri.com
Looking at job offers (both academia and industry) and it’s basically all “AI” & Co. 😔
And WTF is “experience with LLM” for an academic post in epidemiology??
csthiago.bsky.social
I haven't contact them / or post on pubpeer. Someone shared this paper with me today and I found it those bits very strange.
I will email them tomorrow
csthiago.bsky.social
Oh. I haven't paid close attention to this figure. There are even participants starting not at 0%.
About the "rr" is complicated to know, once they have used time varying exposure and idk how to interpret cum incidence in this context.
csthiago.bsky.social
About the RR (relative risk in the paper, not risk ratio), which is the HR is... but to me looks misleading
csthiago.bsky.social
Sleuths,
Can someone explain to me how these CIs are possible?
www.nejm.org/doi/full/10....
It is not clear how they got RR from the Cox PH, as it would require choosing a time point (looks like an interpretation of HR as RR)

@lonnibesancon.bsky.social @sophieehill.bsky.social @retractionwatch.com
csthiago.bsky.social
Thanks! I will take a look
csthiago.bsky.social
2/2
The outcome model has multiple categorical variables; I only found binary and continuous methods in MICE (for mixed models). Any ideas?
#rstats #episky
csthiago.bsky.social
1/2
Does anyone know how to proceed for multiple imputations if one of the variables (fully observed) in the model has more than 5000 levels (in the outcome model, it is a mixed effect)?

#rstats #episky
csthiago.bsky.social
It's also possible to use data.table speed through tidytable (tidyverse syntax)
csthiago.bsky.social
It is very interesting book. The story behind "cleaning" in surgery
csthiago.bsky.social
Almost all self citations in open repositories
csthiago.bsky.social
You can sync WoS to Orcid and let it do the udpates
csthiago.bsky.social
I don't know if that will change in the future (pessimistic hat). Even "traditional" methods still suffer from inadequate peer review, just see the infinitude of papers with time varying exposure/treatment being treated as time fixed and being published in "prestigious" journals
csthiago.bsky.social
I would say that there is nothing special (in terms of wrong things) compared to others fields. Equally wrong everywhere