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.
