Explore >> Select a destination
|
You are here 
|
www.rdatagen.net | ||
| | | | |
aosmith.rbind.io
|
|
| | | | | I walk through an example of simulating data from a binomial generalized linear mixed model with a logit link and then exploring estimates of over/underdispersion. | |
| | | | |
fharrell.com
|
|
| | | | | In randomized clinical trials, power can be greatly increased and sample size reduced by using an ordinal outcome instead of a binary one. The proportional odds model is the most popular model for analyzing ordinal outcomes, and it borrows treatment effect information across outcome levels to obtain a single overall treatment effect as an odds ratio. When deaths can occur, it is logical to have death as one of the ordinal categories. Consumers of the results frequently seek evidence of a mortality reduct... | |
| | | | |
r-video-tutorial.blogspot.com
|
|
| | | | | Power analysis is extremely important in statistics since it allows us to calculate how many chances we have of obtaining realistic result... | |
| | | | |
matthewmcateer.me
|
|
| | | Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space | ||
