prop_med_yreg_logistic

Calculate the approximate proportion mediated on the risk 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_logistic function

<dl><dt>pnde</dt>
<dd>Pure natural direct effect on the log scale.</dd>
<dt>tnie</dt>
<dd>Total natural indirect effect on the log scale.</dd></dl>

Arguments

Calculate the proportion mediated for yreg logistic. — prop_med_yreg_logistic

<dl>

<dt>pnde</dt>
<dd>Pure natural direct effect on the log scale.</dd>


<dt>tnie</dt>
<dd>Total natural indirect effect on the log scale.</dd>

</dl>

prop_med_yreg_logistic: Calculate the proportion mediated for yreg logistic.

Description

Usage

Value

Arguments