| 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) |