Explore >> Select a destination
|
You are here 
|
fharrell.com | ||
| | | | |
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... | |
| | | | |
hbiostat.org
|
|
| | | | | Randomized clinical trials are successful because they do not mimic clinical practice. They remain highly clinically relevant despite this. | |
| | | | |
fharrell.com
|
|
| | | Since the Wilcoxon test is a special case of the proportional odds (PO) model, if one likes the Wilcoxon test, one must like the PO model. This is made more convincing by showing examples of how one may accurately compute the Wilcoxon statistic from the PO model's odds ratio. | ||
