Computes experimental designs for a two-arm experiment with covariates by greedily optimizing a balance objective function. This optimization provides lower variance for the treatment effect estimator (and higher power) while preserving a design that is close to complete randomization. We return all iterations of the designs for use in a permutation test. Additional functionality includes using branch and bound optimization (via Gurobi) and exhaustive enumeration.
|Author||Adam Kapelner, David Azriel and Abba M. Krieger|
|Maintainer||Adam Kapelner <[email protected]edu>|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.