HOW DO YOU DEVELOP A NEW PREDICTION MODEL?

This [THREAD] has been long in the making and is arguably overdue

1/138
I'll assume you have some basic knowledge of prediction models and will be relatively short on the technicalities

lets suppose you interested in developing a prediction model for disease X

2/138
There are probably a few dozen prediction models already developed for disease X!

most of them have never and will never be used

so... are you really, really, really sure the world is waiting for a new prediction model for disease X?

/138
Glad you made it all to the end!

More technical details 👇👇👇👇

138/138

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More from @MaartenvSmeden

16 Sep
the ultimate reviewer #2 bingo card
key citations 👇
unclear analysis aims
stat.berkeley.edu/~aldous/157/Pa…

evidence of absence fallacy
bmj.com/content/311/70…

data dredging
bmj.com/content/311/70…

noisy data fallacy
science.sciencemag.org/content/355/63…
Read 6 tweets
3 Aug
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…

ICYI, I have a few thoughts to share
We were fortunate to have produced @bmj_latest first living review
bmj.com/content/369/bm…
The aim of our review is (and always was) to give an overview and appraisal of currently available diagnosis and prognosis models related to COVID-19

But this is a fast moving field: from 31 models reviewed in April to 145 models reviewed in our 2nd update published in July
Read 14 tweets
11 Jul
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
Read 4 tweets
9 Jun
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

Here are some good arguments by @statsepi:
medium.com/@darren_dahly/…

And some more: medium.com/@darren_dahly/…

3/n
Read 20 tweets
19 May
The definitive guide to COVID-19 prognosis modeling success

1) Do not explain where the data come from (country) or when (study dates) they were obtained. Do not specify inclusion or exclusion criteria
2) Do not define a target group. Talk generically about COVID-19 patients, do not define how they were recruited
3) Do not provide a table with patient characteristics. In particular, do not mention use of medication or co-morbidities
Read 18 tweets
13 Apr
Let's talk about the "risk factors" for COVID-19 for a moment

1/n
We talk about risk factors all the time. Not just in the medical scientific literature: you will find risk factors being discussed in the popular media and on social media too

Exhibit A: nytimes.com/reuters/2020/0…

2/n
The term "risk factor" is popular in medical research. It has been used in literature since at least the 1950s

BUT definitions for what a risk factor really is or should be varies. As this article argues quite convincingly bmj.com/content/355/bm…

3/n
Read 15 tweets

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