dc.contributor.author | Tingley, Dustin | |
dc.contributor.author | Yamamoto, Teppei | |
dc.contributor.author | Hirose, Kentaro | |
dc.contributor.author | Keele, Luke | |
dc.contributor.author | Imai, Kosuke | |
dc.date.accessioned | 2014-10-23T17:27:39Z | |
dc.date.available | 2014-10-23T17:27:39Z | |
dc.date.issued | 2014-08 | |
dc.date.submitted | 2012-06 | |
dc.identifier.issn | 1548-7660 | |
dc.identifier.uri | http://hdl.handle.net.ezproxyberklee.flo.org/1721.1/91154 | |
dc.description.abstract | In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent) mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials. | en_US |
dc.language.iso | en_US | |
dc.publisher | UCLA Statistics/American Statistical Association | en_US |
dc.relation.isversionof | http://www.jstatsoft.org/v59/i05 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/ | en_US |
dc.source | UCLA Statistics/American Statistical Association | en_US |
dc.title | mediation: R package for causal mediation analysis | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Tingley, Dustin,Teppei Yamamoto, Kentaro Hirose, Luke Keele, and Kosuke Imai. "mediation: R package for causal mediation analysis." Journal of Statistical Software Vol. 59, Issue 5 (September 2014). | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Political Science | en_US |
dc.contributor.mitauthor | Yamamoto, Teppei | en_US |
dc.relation.journal | Journal of Statistical Software | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-8079-7675 | |
mit.license | PUBLISHER_CC | en_US |
mit.metadata.status | Complete | |