I’ll start: you can buy an enormous TV from Costco for like $100 bucks now.
Not sure what the right model to fit is? Should you allow random intercepts, slopes, both? What do Bayesian methods say?
Just call {kitchensink::throw} to fit every possible model and see how your results differ!
Not sure what the right model to fit is? Should you allow random intercepts, slopes, both? What do Bayesian methods say?
Just call {kitchensink::throw} to fit every possible model and see how your results differ!
Lancet Respir Med 2025 doi: 10.1016/S2213-2600(25)00054-2. Online ahead of print.
Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill
pubmed.ncbi.nlm.nih.gov/40250459/
Lancet Respir Med 2025 doi: 10.1016/S2213-2600(25)00054-2. Online ahead of print.
Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill
pubmed.ncbi.nlm.nih.gov/40250459/
Cc @kathrinbertschy.bsky.social
Cc @kathrinbertschy.bsky.social
A database I've used for over 30 years
I hope and pray it comes back soon!
A database I've used for over 30 years
I hope and pray it comes back soon!
𝗚𝗲𝘁 𝘄𝗲𝗲𝗸𝗹𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝘀: CanadaHealthwatch.ca/newsletter 🍁
𝗚𝗲𝘁 𝘄𝗲𝗲𝗸𝗹𝘆 𝘂𝗽𝗱𝗮𝘁𝗲𝘀: CanadaHealthwatch.ca/newsletter 🍁
Translation in alt
Translation in alt
That "immortal time" is so frequent in survival analyses for #causalinference is fascinating.
Because "immortal time" doesn't exist in the data, *we* create it when misanalyzing the data.
Our new paper pubmed.ncbi.nlm.nih.gov/39494894/ summarizes why immortal time arises & how to prevent it.
That "immortal time" is so frequent in survival analyses for #causalinference is fascinating.
Because "immortal time" doesn't exist in the data, *we* create it when misanalyzing the data.
Our new paper pubmed.ncbi.nlm.nih.gov/39494894/ summarizes why immortal time arises & how to prevent it.