/explore
|
You are here 
|
fharrell.com | ||
| | | | |
lesslikely.com
|
|
| | | | | A look at how an influential meta-analysis continues to be cited widely when it contains a major error that has gone unnoticed. | |
| | | | |
www.fharrell.com
|
|
| | | | | Observational data from electronic health records may contain biases that large sample sizes do not overcome. Moderate confounding by indication may render an infinitely large observational study less useful than a small randomized trial for estimating relative treatment effectiveness. | |
| | | | |
errorstatistics.com
|
|
| | | | | Stephen Senn Head of Competence Center for Methodology and Statistics (CCMS) Luxembourg Institute of Health Twitter @stephensenn Being a statistician means never having to say you are certain A recent discussion of randomised controlled trials[1] by Angus Deaton and Nancy Cartwright (D&C) contains much interesting analysis but also, in my opinion, does not escape rehashing... | |
| | | | |
jembendell.com
|
|
| | | Hello, fellow participants in the Metacrisis Meetings Initiative, Our last meeting on how larger forests and healthier oceans can help cool the climate was both well attended and lively, continuing to indicate to me that this salon will be useful to many of us. As I mentioned in my last post, at the next meeting... | ||
