Packaged: 2018-06-18 19:11:56 UTC; mblackwell

Description: A package to study how various assumptions about selection
bias affects estimates of causal effects.
Packaged: 2013-04-21 17:27:12 UTC; mblackwell

Title: Causal Inference Based on Weighting Estimators
Description: Various estimation methods for causal inference based on inverse probability weighting. Specifically, the package includes methods for estimating average treatment effects as well as direct and indirect effects in causal mediation analysis. The models refer to the studies of Frölich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, and Frölich and Huber (2017) <doi:10.1111/rssb.12232>.
Collate: 'functions.R' 'medweight.R' 'treatweight.R' 'lateweight.R'
Packaged: 2018-02-22 21:50:29 UTC; HSG-Spezial

Title: Estimation Methods for Causal Inference Based on Inverse
Packaged: 2018-08-01 10:11:20 UTC; HSG-Spezial

Description: Various estimation methods for causal inference based on inverse probability weighting. Specifically, the package includes methods for estimating average treatment effects as well as direct and indirect effects in causal mediation analysis. The models refer to the studies of Froelich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, and Froelich and Huber (2017) <doi:10.1111/rssb.12232>.
Packaged: 2018-12-01 14:15:50 UTC; HSG-Spezial

Depends: R (>= 3.5.0), mvtnorm, np, LARF, hdm

Title: Causal Inference Based on Inverse Probability Weighting, Doubly
Robust Estimation, and Double Machine Learning
Description: Various estimators of causal effects based on inverse probability weighting, doubly robust estimation, and double machine learning. Specifically, the package includes methods for estimating average treatment effects, direct and indirect effects in causal mediation analysis, and dynamic treatment effects. The models refer to studies of Froelich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, Froelich and Huber (2017) <doi:10.1111/rssb.12232>, Hsu, Huber, Lee, and Lettry (2020)  <doi:10.1002/jae.2765>, and others.
Imports: mvtnorm, np, LARF, hdm, SuperLearner, glmnet, ranger, xgboost,