propensityml-package: propensityml: Propensity score weighting using machine...
In ygeunkim/propensityml: Propensity score weighting using machine learning methods
Description
Details
Author(s)
References
See Also
Description
Implement machine learning models to improve propensity score weight,
especially tree models, e.g.
CART, pruned CART, random forests, etc.
Details
The propensityml package provides various ML functions to estimate propensity score.
Author(s)
Maintainer: Young Geun Kim dudrmshub@gmail.com
References
Lee, B. K., Lessler, J., & Stuart, E. A. (2010). Improving propensity score weighting using machine learning. Statistics in Medicine. Statistics in Medicine, 29(3), 337-346.
See Also
Useful links:
ygeunkim/propensityml documentation built on Jan. 1, 2021, 1:44 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Details Author(s) References See Also
Description
Implement machine learning models to improve propensity score weight, especially tree models, e.g. CART, pruned CART, random forests, etc.
Details
The propensityml package provides various ML functions to estimate propensity score.
Author(s)
Maintainer: Young Geun Kim dudrmshub@gmail.com
References
Lee, B. K., Lessler, J., & Stuart, E. A. (2010). Improving propensity score weighting using machine learning. Statistics in Medicine. Statistics in Medicine, 29(3), 337-346.
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.