R: Correcting Misclassified Mediation Analysis

# Correcting Misclassified Mediation Analysis

## Documentation for package ‘COMMA’ version 1.1.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

COMBO_EM_algorithm | EM-Algorithm Estimation of the Binary Outcome Misclassification Model
COMBO_EM_function | EM-Algorithm Function for Estimation of the Misclassification Model
COMBO_weight | Compute E-step for Binary Outcome Misclassification Model Estimated With the EM-Algorithm
COMMA_boot_sample | Generate Bootstrap Samples for Estimating Standard Errors
COMMA_data | Generate Data to use in COMMA Functions
COMMA_EM | EM Algorithm Estimation of the Binary Mediator Misclassification Model
COMMA_EM_bootstrap_SE | Estimate Bootstrap Standard Errors using EM
COMMA_OLS | Ordinary Least Squares Estimation of the Binary Mediator Misclassification Model
COMMA_OLS_bootstrap_SE | Estimate Bootstrap Standard Errors using OLS
COMMA_PVW | Predictive Value Weighting Estimation of the Binary Mediator Misclassification Model
COMMA_PVW_bootstrap_SE | Estimate Bootstrap Standard Errors using PVW
EM_function_bernoulliY | EM Algorithm Function for Estimation of the Misclassification Model
EM_function_bernoulliY_XM | EM Algorithm Function for Estimation of the Misclassification Model
EM_function_normalY | EM Algorithm Function for Estimation of the Misclassification Model
EM_function_normalY_XM | EM Algorithm Function for Estimation of the Misclassification Model
EM_function_poissonY | EM Algorithm Function for Estimation of the Misclassification Model
EM_function_poissonY_XM | EM Algorithm Function for Estimation of the Misclassification Model
misclassification_prob | Compute Conditional Probability of Observed Mediator Given True Mediator, for Every Subject
NCHS2022_sample | Example data from the National Vital Statistics System of the National Center for Health Statistics (NCHS), 2022
pistar_compute | Compute Conditional Probability of Each Observed Outcome Given Each True Outcome, for Every Subject
pi_compute | Compute Probability of Each True Outcome, for Every Subject
sum_every_n | Sum Every "n"th Element
sum_every_n1 | Sum Every "n"th Element, then add 1
theta_optim | Likelihood Function for Normal Outcome Mechanism with a Binary Mediator
theta_optim_XM | Likelihood Function for Normal Outcome Mechanism with a Binary Mediator and an Interaction Term
true_classification_prob | Compute Probability of Each True Mediator, for Every Subject
w_m_binaryY | Compute E-step for Binary Mediator Misclassification Model Estimated With the EM Algorithm
w_m_normalY | Compute E-step for Binary Mediator Misclassification Model Estimated With the EM Algorithm
w_m_poissonY | Compute E-step for Binary Mediator Misclassification Model Estimated With the EM Algorithm