Targeted Maximum Likelihood Estimation


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Documentation for package ‘tmle’ version 2.0.0

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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)