First, I send you emails to which you politely and quickly responded. Thanks. You seemed to agree with my critique, but you didn't show any initiative to change it or remove the model
@Laconic_doc@statsmethods@GSCollins Second, I am one of the authors of a reply to the OpenSAFELY study where we specifically mention their model falls short of developing a risk model. You seem to have ignored that and used their multivariable results anyway
@Laconic_doc@statsmethods@GSCollins Third, I am the senior author on a living review on diagnostic and prognostic models for COVID. We have been warning about bad prognostic modeling since March. You seem to be familiar with the publication, but you didn't pick up on the modeling advice bmj.com/content/369/bm…
@Laconic_doc@statsmethods@GSCollins I don't know what more to do to stop models that are poorly developed and not validated to become publicly available or even used.
I'm sure you do not intend to do harm, but we know that bad prediction models *can* do harm, no matter how well intended they are
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The BMJ just published an editorial about living systematic reviews worth a read, which is new territory for just about everyone bmj.com/content/370/bm…
Used to get annoyed by stats consult clients who insisted they needed machine learning for their very large dataset (N of 100s or few 1000s). Now I tell them logistic regression *is* machine learning and everything is great again
And since machine learning is a sub field of AI, logistic regression is also AI. I should have understood this sooner
Logistic regression as statistical model
- prepare data
- estimate model
- evaluate performance
- report
Logistic regression as machine learning
- prepare data
- estimate model
- evaluate performance
- report
Was asked for personal favorite resources for improving methods and statistics skills. I promised to make it a thread, so here it is
1/n
I work in medical research, so that is going to be my focus here too. But I’d like to think the resources are relevant to a wider audience
This list should not be taken as a guide to become a statistician, nor is it a must-read list for all academics (obviously)
2/n
My personal view is that medical research would benefit from involving trained statisticians earlier and more frequently; not from everyone trying to become one