mediation: R package for causal mediation analysis
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 a...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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UCLA Statistics/American Statistical Association
2014
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| Online Access: | http://hdl.handle.net/1721.1/91154 https://orcid.org/0000-0002-8079-7675 |
| _version_ | 1811095442651348992 |
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| author | Tingley, Dustin Yamamoto, Teppei Hirose, Kentaro Keele, Luke Imai, Kosuke |
| author2 | Massachusetts Institute of Technology. Department of Political Science |
| author_facet | Massachusetts Institute of Technology. Department of Political Science Tingley, Dustin Yamamoto, Teppei Hirose, Kentaro Keele, Luke Imai, Kosuke |
| author_sort | Tingley, Dustin |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T16:16:50Z |
| format | Article |
| id | mit-1721.1/91154 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:16:50Z |
| publishDate | 2014 |
| publisher | UCLA Statistics/American Statistical Association |
| record_format | dspace |
| spelling | mit-1721.1/911542022-09-29T19:20:09Z mediation: R package for causal mediation analysis Tingley, Dustin Yamamoto, Teppei Hirose, Kentaro Keele, Luke Imai, Kosuke Massachusetts Institute of Technology. Department of Political Science Yamamoto, Teppei 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. 2014-10-23T17:27:39Z 2014-10-23T17:27:39Z 2014-08 2012-06 Article http://purl.org/eprint/type/JournalArticle 1548-7660 http://hdl.handle.net/1721.1/91154 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). https://orcid.org/0000-0002-8079-7675 en_US http://www.jstatsoft.org/v59/i05 Journal of Statistical Software Creative Commons Attribution http://creativecommons.org/licenses/by/3.0/ application/pdf UCLA Statistics/American Statistical Association UCLA Statistics/American Statistical Association |
| spellingShingle | Tingley, Dustin Yamamoto, Teppei Hirose, Kentaro Keele, Luke Imai, Kosuke mediation: R package for causal mediation analysis |
| title | mediation: R package for causal mediation analysis |
| title_full | mediation: R package for causal mediation analysis |
| title_fullStr | mediation: R package for causal mediation analysis |
| title_full_unstemmed | mediation: R package for causal mediation analysis |
| title_short | mediation: R package for causal mediation analysis |
| title_sort | mediation r package for causal mediation analysis |
| url | http://hdl.handle.net/1721.1/91154 https://orcid.org/0000-0002-8079-7675 |
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