effects: Functions to calculate natural direct and indirect effects.

In sensmediation: Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects

Description

Functions used to calculate natural direct and indirect effects based on the estimated regression parameters. Called by calc.effects. The functions are named according to the convention eff."mediator model type""outcome model type" where b stands for binary probit regression and c stands for linear regression.

Usage

eff.bb(Rho, betas, thetas, x.med, x.out, alt.decomposition, exp.value,
  control.value)

eff.bc(Rho, betas, thetas, x.med, x.out, alt.decomposition, exp.value,
  control.value)

eff.cb(Rho, betas, thetas, sigma.eta, x.med, x.out, alt.decomposition,
  exp.value, control.value)

eff.cc(Rho, betas, thetas, x.med, x.out, alt.decomposition, exp.value,
  control.value)

Arguments

Rho	The sensitivity parameter vector.
betas	List of mediator regression parameters
thetas	List of outcome regression parameters
x.med	Mediator covariate matrix for which to calculate standard errors
x.out	Outcome covariate matrix for which to calculate standard errors
alt.decomposition	logical indicating whether or not alternative definitions of the direct and indirect effects should be used.
exp.value	value of the exposure variable used as the exposure condition.
control.value	value of the exposure variable used as the control (unexposed) condition.
sigma.eta	For a continuous mediator and binary outcome, matrix with the estimated residual standard deviation for the mediator model over the range of Rho.

sensmediation documentation built on June 3, 2019, 9:02 a.m.