Showing 2 of total 2 results (show query)
michaellli
evalITR:Evaluating Individualized Treatment Rules
Provides various statistical methods for evaluating Individualized Treatment Rules under randomized data. The provided metrics include Population Average Value (PAV), Population Average Prescription Effect (PAPE), Area Under Prescription Effect Curve (AUPEC). It also provides the tools to analyze Individualized Treatment Rules under budget constraints. Detailed reference in Imai and Li (2019) <arXiv:1905.05389>.
Maintained by Michael Lingzhi Li. Last updated 2 years ago.
14 stars 6.78 score 36 scripts
kosukeimai
experiment:R Package for Designing and Analyzing Randomized Experiments
Provides various statistical methods for designing and analyzing randomized experiments. One functionality of the package is the implementation of randomized-block and matched-pair designs based on possibly multivariate pre-treatment covariates. The package also provides the tools to analyze various randomized experiments including cluster randomized experiments, two-stage randomized experiments, randomized experiments with noncompliance, and randomized experiments with missing data.
Maintained by Kosuke Imai. Last updated 3 years ago.
14 stars 5.29 score 23 scripts