prop_med_yreg_linear

Calculate the proportion mediated on the mean difference scale.

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.

Yi Li

regmedint

Regression-Based Causal Mediation Analysis with Interaction and
Effect Modification Terms

Kazuki Yoshida

Maya Mathur

prop_med_yreg_linear function

<dl><dt>pnde</dt>
<dd>Pure natural direct effect.</dd>
<dt>tnie</dt>
<dd>Total natural indirect effect.</dd></dl>

Arguments

Calculate the proportion mediated for yreg linear. — prop_med_yreg_linear

<dl>

<dt>pnde</dt>
<dd>Pure natural direct effect.</dd>


<dt>tnie</dt>
<dd>Total natural indirect effect.</dd>

</dl>

prop_med_yreg_linear: Calculate the proportion mediated for yreg linear.

Description

Usage

Value

Arguments