mediation: R Package for Causal Mediation Analysis , mediation is a publicly available R package that allows both parametric and nonparametric causal mediation analysis. It implements the methods and suggestions in Imai, Keele, and Yamamoto (2010) and Imai, Keele, Tingley (2010). In addition to the estimation of causal mediation effects, the software also allows researchers to conduct sensitivity analysis for certain parametric models. (Source:

References in zbMATH (referenced in 11 articles , 1 standard article )

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  1. Mair, Patrick: Modern psychometrics with R (2018)
  2. Johan Steen and Tom Loeys and Beatrijs Moerkerke and Stijn Vansteelandt: medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models (2017) not zbMATH
  3. Kim, Chanmin; Daniels, Michael J.; Marcus, Bess H.; Roy, Jason A.: A framework for Bayesian nonparametric inference for causal effects of mediation (2017)
  4. Qingzhao Yu, Bin Li: mma: An R Package for Mediation Analysis with Multiple Mediators (2017) not zbMATH
  5. Santtu Tikka and Juha Karvanen: Identifying Causal Effects with the R Package causaleffect (2017) not zbMATH
  6. Albert, Jeffrey M.; Geng, Cuiyu; Nelson, Suchitra: Causal mediation analysis with a latent mediator (2016)
  7. Bailey, Drew H.; Zhou, Xinlin; Zhang, Yiyun; Cui, Jiaxin; Fuchs, Lynn S.; Jordan, Nancy C.; Gersten, Russell; Siegler, Robert S.: Development of fraction concepts and procedures in U.S. and Chinese children (2015) MathEduc
  8. Sidney, Pooja G.; Hattikudur, Shanta; Alibali, Martha W.: How do contrasting cases and self-explanation promote learning? Evidence from fraction division (2015) MathEduc
  9. Dustin Tingley; Teppei Yamamoto; Kentaro Hirose; Luke Keele; Kosuke Imai: mediation: R Package for Causal Mediation Analysis (2014) not zbMATH
  10. Imai, Kosuke; Keele, Luke; Yamamoto, Teppei: Identification, inference and sensitivity analysis for causal mediation effects (2010)
  11. Wollschläger, Daniel: Foundations of data analysis with R. An application oriented introduction. (2010)