| 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) |