regmedint

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.

Last 30 days

This package has been downloaded 314 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 times.

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

This package has been downloaded 3,898 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 43 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.