R: Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects

# Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects

## Documentation for package ‘sensmediation’ version 0.3.1

- DESCRIPTION file
- Package NEWS

## Help Pages

calc.effects | Function for estimation of natural direct and indirect effects and sensitivity analysis for unobserved mediator-outcome confounding
coefs.sensmed | ML estimation of regression parameters for calculation of direct and indirect effects under unobserved confounding
eff.bb | Functions to calculate natural direct and indirect effects.
eff.bc | Functions to calculate natural direct and indirect effects.
eff.cb | Functions to calculate natural direct and indirect effects.
eff.cc | Functions to calculate natural direct and indirect effects.
effects | Functions to calculate natural direct and indirect effects.
grr | Analytic gradients of the loglikelihood functions for ML estimation of regression parameters
grr.bb | Analytic gradients of the loglikelihood functions for ML estimation of regression parameters
grr.bc | Analytic gradients of the loglikelihood functions for ML estimation of regression parameters
grr.cb | Analytic gradients of the loglikelihood functions for ML estimation of regression parameters
grr.cc | Analytic gradients of the loglikelihood functions for ML estimation of regression parameters
hess | Analytic Hessians of the loglikelihood functions for ML estimation of regression parameters
hess.bb | Analytic Hessians of the loglikelihood functions for ML estimation of regression parameters
hess.bc | Analytic Hessians of the loglikelihood functions for ML estimation of regression parameters
hess.cb | Analytic Hessians of the loglikelihood functions for ML estimation of regression parameters
hess.cc | Analytic Hessians of the loglikelihood functions for ML estimation of regression parameters
LogL | Implementation of loglikelihood functions for ML estimation of regression parameters
LogL.bb | Implementation of loglikelihood functions for ML estimation of regression parameters
LogL.bc | Implementation of loglikelihood functions for ML estimation of regression parameters
LogL.cb | Implementation of loglikelihood functions for ML estimation of regression parameters
LogL.cc | Implementation of loglikelihood functions for ML estimation of regression parameters
ML | Functions for ML estimation of regression parameters for sensitivity analysis
ML.bb | Functions for ML estimation of regression parameters for sensitivity analysis
ML.bc | Functions for ML estimation of regression parameters for sensitivity analysis
ML.cb | Functions for ML estimation of regression parameters for sensitivity analysis
ML.cc | Functions for ML estimation of regression parameters for sensitivity analysis
more.effects | Estimate additional natural direct and indirect effects based on an '"effectsMed"' object
partdevs | Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).
partdevs.bb | Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).
partdevs.bc | Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).
partdevs.cb | Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).
partdevs.cc | Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).
plot.effectsMed | Plot function for objects of class '"effectsMed"'
print.summaryeffectsMed | Summary function for objects of class '"effectsMed"'
RSdata | Example data for the functions in sensmediation
sensmediation | Estimate natural direct and indirect effects based on parametric regression models and perform sensitivity analysis
stderr.bb | Functions to calculate standard errors of the direct, indirect and total effects using the delta method.
stderr.bc | Functions to calculate standard errors of the direct, indirect and total effects using the delta method.
stderr.cb | Functions to calculate standard errors of the direct, indirect and total effects using the delta method.
stderr.cc | Functions to calculate standard errors of the direct, indirect and total effects using the delta method.
stderrs | Functions to calculate standard errors of the direct, indirect and total effects using the delta method.
summary.effectsMed | Summary function for objects of class '"effectsMed"'