Why most studies into COVID19 risk factors may be producing flawed conclusions - and how to fix the problem
wherearethenumbers.substack.com
In a new paper we extend the recent work by Griffith et al which highlights how ‘collider bias’ in studies of COVID19 undermines our understanding of the disease risk and severity. This is typically caused by the data being restricted to people who have undergone COVID19 testing, among whom healthcare workers are over-represented. For example, collider bias caused by smokers being under-represented in the dataset may (at least partly) explain recent empirical results that suggest smoking reduces the risk of COVID19.
Why most studies into COVID19 risk factors may be producing flawed conclusions - and how to fix the problem
Why most studies into COVID19 risk factors…
Why most studies into COVID19 risk factors may be producing flawed conclusions - and how to fix the problem
In a new paper we extend the recent work by Griffith et al which highlights how ‘collider bias’ in studies of COVID19 undermines our understanding of the disease risk and severity. This is typically caused by the data being restricted to people who have undergone COVID19 testing, among whom healthcare workers are over-represented. For example, collider bias caused by smokers being under-represented in the dataset may (at least partly) explain recent empirical results that suggest smoking reduces the risk of COVID19.