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Corey Scholes @lastbarbender.bsky.social · 2d

Old mate went truly all in on in that round

Fraud in army - bold strategy at any time
Fraud as an Other Rank
Crime in early 20th century (what is rehabilitation?)
Combine all of those things and then do it in wartime...

Corey Scholes @lastbarbender.bsky.social · 3d

"Model failed to converge"

#rstats #medsky #statsky

🏰meg⚔️ @Birthright Audiobook! @impavid.us · 6d

In honor of spooky month, share a 4 word horror story that only someone in your profession would understand

I'll go first: Six page commercial lease.

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Reposted by Corey Scholes

Matthew Facciani @matthewfacciani.bsky.social · 5d

Can we actually train ourselves to be more open-minded and harder to fool?

New research says yes. A short message warning us about closed-mindedness made people better at spotting misinformation, less likely to believe conspiracy theories, and more thoughtful about what they shared #MisinfoResearch

How to Train Yourself to Be More Open-Minded and Less Easily Misled

New research shows that cultivating open-minded thinking can be taught, and that this simple shift improves our ability to tell facts from falsehoods.

matthewfacciani.substack.com

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Reposted by Corey Scholes

Prof Sam Illingworth @samillingworth.com · 8d

🌧️ Forest loss and flooding

A new study shows that deforestation and forest fires in Australia reduce rainfall interception, increasing river flooding across vast regions.

🔗 www.nature.com/articles/s43...

#SciComm #ClimateCrisis #Floods 🧪

Interception reduction from deforestation and forest fire increases large-scale fluvial flooding risk - Communications Earth & Environment

Forest coverage loss from wildfires and deforestation increases flood risk for large-scale river catchments by reducing interception, according to analysis of data from twenty-one watersheds in Australia.

www.nature.com

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Corey Scholes @lastbarbender.bsky.social · 9d

I think Moriarity had had some particularly bad experiences with German tanks in the bocage though

Corey Scholes @lastbarbender.bsky.social · 12d

This is the way

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Corey Scholes @lastbarbender.bsky.social · 12d

First episode our hero (or Xena-esque heroine) comes up against an ortho bro|sis cartel pushing out some dubious "trials" on their new pet surgical techniques that they are introducing in young athletes. There are strong echoes of the Terminal List when one of the athletes joins in the hunt.

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Corey Scholes @lastbarbender.bsky.social · 12d

Kicking in doors on hospital Research Offices and pushing the envelope on kidnapping and false imprisonment to hrec chairs that have allowed dubious methods through the approval process.

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Corey Scholes @lastbarbender.bsky.social · 12d

I think a Reacher + The Accountant remake is needed - a drifter statistician with an outrageous physique moving from one random hospital to the next, breaking up clinical research cartels and applying high levels of violence to restore appropriate rigour to studies in their early phases of set-up.

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Corey Scholes @lastbarbender.bsky.social · 13d

I spend an inordinate amount of time explaining the relationship between inc-exc criteria and the recruitment flowchart - "yes but who are you excluding AFTER you initially included them?"

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Corey Scholes @lastbarbender.bsky.social · 15d

the strictness of forcats upfront saves so much hassle downstream...nothing worse than untangling factors several models down the way

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Corey Scholes @lastbarbender.bsky.social · 15d

I should add some tags so it comes up on feeds

#rstats #statsky #clinicalresearch #whatislove

Corey Scholes @lastbarbender.bsky.social · 15d

The options I see are - run everything with a subset + impute approach, ignoring the advantages of the reverse approach; use complete case analysis for the flowchart and descriptives (risking a disconnect with the model dataset and results) or there is a way of working with mids for every step?

Corey Scholes @lastbarbender.bsky.social · 15d

The purpose of imputation is to input into the inferential modeling step (what effect does x variable have on y outcome?) but if the imputation is upstream of the sample selection I need to figure out how to work with a mids object for generating descriptive summaries + the recruitment flow chart

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Corey Scholes @lastbarbender.bsky.social · 15d

For background I am aligning to the RECORD reporting guidelines in a quarto document within Rstudio. This means if I move the imputation step from where it is in the pipeline currently (RECORD 12.2 data cleaning) to upstream (RECORD 6.1 sample selection) - I am going to have some...complications

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Corey Scholes @lastbarbender.bsky.social · 15d

Thanks to everyone that weighed in on this - there are some strong arguments for imputing first and then subsetting, especially when the subsetting variable set contains missingness.

But I am wrestling with how to implement this across the entire analysis pipeline in practice.

Corey Scholes @lastbarbender.bsky.social · 24d

Ok #skyhivemind and #statsky #rstats - I am analysing a subset from a clinical quality registry. Both the total registry dataset and the subset have missing data that needs to be imputed. Should I i) impute the full registry set and then subset or ii) subset from the get-go and discard the rest?

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Corey Scholes @lastbarbender.bsky.social · 18d

Dammit, you beat me to the reply

Corey Scholes @lastbarbender.bsky.social · 19d

Starting a thread like this with this level of heresy needs to come with a warning label

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Corey Scholes @lastbarbender.bsky.social · 22d

I think this is a separate question to the one I'm asking for this analysis, but would be open to collaborating with others on a more methods paper

Corey Scholes @lastbarbender.bsky.social · 24d

ah ha there is always a paper...practically there is missingness in the subset variables (although it could be argued away), so it looks like impute-then-subset.

The major downside being how complicated this analysis file is going to become!

Thanks for weighing in!

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Corey Scholes @lastbarbender.bsky.social · 24d

subsetting based on patient characteristics

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Corey Scholes @lastbarbender.bsky.social · 24d

Ok #skyhivemind and #statsky #rstats - I am analysing a subset from a clinical quality registry. Both the total registry dataset and the subset have missing data that needs to be imputed. Should I i) impute the full registry set and then subset or ii) subset from the get-go and discard the rest?

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Corey Scholes @lastbarbender.bsky.social · Sep 12

So if you're a student, doctor or an established surgeon submitting papers and either getting rejected or taking ages through review, start at the start and change the way you are framing what you are asking right from the planning stage.
#publishing #orthopaedics

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Corey Scholes @lastbarbender.bsky.social · Sep 12

Getting the question nailed down into a structured statement has other benefits for the keen writer, in that many of the other sections are much easier to draft and get right the first go. More importantly, it will elevate the exchange you have with a reviewer!

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Corey Scholes @lastbarbender.bsky.social · Sep 12

If I cant refer to a clear question constantly through a review, it's impossible to judge whether any of the other parts of the paper are appropriate to what you have asked. Often, the papers I receive have an implied question or something like "evaluate outcomes after surgical procedure x".

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