R: Targeted Maximum Likelihood Estimation

# Targeted Maximum Likelihood Estimation

## Documentation for package ‘tmle’ version 2.1.1

- DESCRIPTION file
- Package NEWS

## Help Pages

tmle-package | Targeted Maximum Likelihood Estimation with Super Learning
calcParameters | Calculate Parameter Estimates (calcParameters)
calcSigma | Calculate Variance-Covariance Matrix for MSM Parameters (calcSigma)
estimateG | Estimate Treatment or Missingness Mechanism
estimateQ | Initial Estimation of Q portion of the Likelihood
fev | Forced Expiratory Volume (FEV) Data (fev)
oneStepATT | Calculate Additive treatment effect among the treated (oneStepATT)
predict.tmle.SL.dbarts2 | Super Learner wrappers for modeling and prediction using 'bart' in the 'dbarts' package
print.summary.tmle | Summarization of the results of a call to the tmle routine
print.summary.tmle.list | Summarization of the results of a call to the tmle routine
print.summary.tmleMSM | Summarization of the results of a call to the tmleMSM function
print.tmle | Summarization of the results of a call to the tmle routine
print.tmle.list | Summarization of the results of a call to the tmle routine
print.tmleMSM | Summarization of the results of a call to the tmleMSM function
summary.tmle | Summarization of the results of a call to the tmle routine
summary.tmle.list | Summarization of the results of a call to the tmle routine
summary.tmleMSM | Summarization of the results of a call to the tmleMSM function
tmle | Targeted Maximum Likelihood Estimation
tmle.SL.dbarts.k.5 | Super Learner wrappers for modeling and prediction using 'bart' in the 'dbarts' package
tmle.SL.dbarts2 | Super Learner wrappers for modeling and prediction using 'bart' in the 'dbarts' package
tmleMSM | Targeted Maximum Likelihood Estimation of Parameter of MSM
tmleNews | Show the NEWS file (tmleNews)