regmedint
Regression-Based Causal Mediation Analysis with Interaction and Effect Modification Terms
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.
- Version1.0.1
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release01/13/2024
Documentation
- VignetteIntroduction to user interface functions
- VignetteImplementation of formulas
- VignetteUsing bootstrapping with regemedint
- VignetteUsing multiple imputation with regmedint
- VignetteImplementation of extended formulas when there are effect measure modifiers
- VignetteValidation of extended formuals with effect modification using bootstrap
- MaterialNEWS
- In ViewsCausalInference
Team
Yi Li
MaintainerShow author detailsKazuki Yoshida
Show author detailsRolesContributor, AuthorMaya Mathur
Show author detailsRolesContributor
Insights
Last 30 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports6 packages
- Suggests17 packages