High-Performance Open-Source Archive
Functions to implement the stability controlled quasi-experiment (SCQE) approach to study the effects of newly adopted treatments that were not assigned at random. This package contains tools to help users avoid making statistical assumptions that rely on infeasible assumptions. Methods developed in Hazlett (2019) <doi:10.1002/sim.8717>.
| Version: | 1.0.0 |
| Imports: | AER, ggplot2, stats, utils |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2021-05-14 |
| DOI: | 10.32614/CRAN.package.scqe |
| Author: | Kirsten Landsiedel [cre], Hazlett Chad [aut], Wulf Ami [ctr], Pinkelman Colleen [ctr], Christopher Gandrud [ctr] |
| Maintainer: | Kirsten Landsiedel <kirstenlandsiedel at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | scqe results |
| Reference manual: | scqe.html , scqe.pdf |
| Package source: | scqe_1.0.0.tar.gz |
| Windows binaries: | r-devel: scqe_1.0.0.zip, r-release: scqe_1.0.0.zip, r-oldrel: scqe_1.0.0.zip |
| macOS binaries: | r-release (arm64): scqe_1.0.0.tgz, r-oldrel (arm64): scqe_1.0.0.tgz, r-release (x86_64): scqe_1.0.0.tgz, r-oldrel (x86_64): scqe_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=scqe to link to this page.
Need mirroring services?
Contact our team at info@vpspulse.com.
Mirror powered by VPSpulse
Infrastructure sponsored by VPSPulse & Secure Payments by ArionPay.