This is an extension of the regression-based causal mediation analysis first proposed by Valeri and VanderWeele (2013) <doi:10.1037/a0031034> and Valeri and VanderWeele (2015) <doi:10.1097/EDE.0000000000000253>). It supports including effect measure modification by covariates(treatment-covariate and mediator-covariate product terms in mediator and outcome regression models) as proposed by Li et al (2023) <doi:10.1097/EDE.0000000000001643>. It also accommodates the original 'SAS' macro and 'PROC CAUSALMED' procedure in 'SAS' when there is no effect measure modification. Linear and logistic models are supported for the mediator model. Linear, logistic, loglinear, Poisson, negative binomial, Cox, and accelerated failure time (exponential and Weibull) models are supported for the outcome model.
Version: 1.0.1 Depends: R (≥ 2.10) Imports: Deriv, MASS, Matrix, assertthat, sandwich, survival Suggests: boot, furrr, future, geepack, knitr, mice, mitools, modelr, purrr, rlang, rmarkdown, stringr, testthat, tidyverse, magic, formattable, kableExtra Published: 2024-01-13 DOI: 10.32614/CRAN.package.regmedint Author: Kazuki Yoshida [ctb, aut], Yi Li [cre, aut], Maya Mathur [ctb] Maintainer: Yi Li <yi.li10 at mail.mcgill.ca> BugReports: https://github.com/kaz-yos/regmedint/issues License: GPL-2 URL: https://kaz-yos.github.io/regmedint/ NeedsCompilation: no Materials: NEWS In views: CausalInference CRAN checks: regmedint results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=regmedint to link to this page.
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