partdevs: Implementations of the partial derivatives (gradients) of the...

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

Description

Functions implementing the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. These are then used to calculate standard errors of the effects using the delta method. Called by the stderrs functions. The functions are named according to the convention partdevs."mediator model type""outcome model type" where bstands for binary probit regression and c stands for linear regression.

Usage

partdevs.bb(beta0, beta1, beta2, beta3, theta0, theta1, theta2, theta3,
  theta4, theta5, theta6, theta7, x.med, x.out, t.de, t.ie, exp.value,
  control.value)

partdevs.bc(beta0, beta1, beta2, beta3, theta2, theta3, theta6, theta7,
  x.med, x.out, t.de, t.ie, exp.value, control.value)

partdevs.cb(beta0, beta1, beta2, beta3, theta0, theta1, theta2, theta3,
  theta4, theta5, theta6, theta7, sigma.eta, x.med, x.out, t.de, t.ie,
  exp.value, control.value)

partdevs.cc(beta0, beta1, beta2, beta3, theta2, theta3, theta6, theta7,
  exp.value, control.value, x.med, x.out, t.de, t.ie)

Arguments

beta0, beta1	Vectors of mediator regression parameters (intercept and exposure) over Rho
beta2, beta3	Matrices of mediator regression parameters (covariate main effects and exposure-covariate interactions) over Rho
theta0, theta1, theta2, theta3	Vectors of outcome regression parameters (intercept, exposure, mediator, exposure-mediator interaction) over Rho
theta4, theta5, theta6, theta7	Matrices of outcome regression parameters (covariate main effects, exposure-covariate, mediator-covariate and exposure-mediator-covariate interactions) over Rho
x.med	Mediator covariate matrix for which to calculate standard errors
x.out	Outcome covariate matrix for which to calculate standard errors
t.de, t.ie	exposure values used to calculate the direct and indirect effects depending on the desired decomposition (see the Details section of sensmediation for more information). If alt.decomposition = TRUE then t.de = exp.value and t.ie = control.value, otherwise t.de = control.value and t.ie = exp.value.
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.