A collection of randomization tests, data sets and examples. The current version focuses on two testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2017)
|Author||Mauricio Olivares-Gonzalez [aut, cre], Ignacio Sarmiento-Barbieri [aut]|
|Maintainer||Mauricio Olivares-Gonzalez <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on GitHub|
Install the latest version of this package by entering the following in R:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.