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tmle (version 2.0.1.1)

Targeted Maximum Likelihood Estimation

Description

Targeted maximum likelihood estimation of point treatment effects (Targeted Maximum Likelihood Learning, The International Journal of Biostatistics, 2(1), 2006. This version automatically estimates the additive treatment effect among the treated (ATT) and among the controls (ATC). The tmle() function calculates the adjusted marginal difference in mean outcome associated with a binary point treatment, for continuous or binary outcomes. Relative risk and odds ratio estimates are also reported for binary outcomes. Missingness in the outcome is allowed, but not in treatment assignment or baseline covariate values. The population mean is calculated when there is missingness, and no variation in the treatment assignment. The tmleMSM() function estimates the parameters of a marginal structural model for a binary point treatment effect. Effect estimation stratified by a binary mediating variable is also available. An ID argument can be used to identify repeated measures. Default settings call 'SuperLearner' to estimate the Q and g portions of the likelihood, unless values or a user-supplied regression function are passed in as arguments.

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Install

install.packages('tmle')

Monthly Downloads

723

Version

2.0.1.1

License

BSD_3_clause + file LICENSE | GPL-2

Maintainer

Last Published

May 28th, 2024

Functions in tmle (2.0.1.1)

summary.tmleMSM

Summarization of the results of a call to the tmleMSM function
tmle

Targeted Maximum Likelihood Estimation
fev

Forced Expiratory Volume (FEV) Data (fev)
tmle-package

Targeted Maximum Likelihood Estimation with Super Learning
oneStepATT

Calculate Additive treatment effect among the treated (oneStepATT)
calcSigma

Calculate Variance-Covariance Matrix for MSM Parameters (calcSigma)
summary.tmle

Summarization of the results of a call to the tmle routine
calcParameters

Calculate Parameter Estimates (calcParameters)
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)
estimateG

Estimate Treatment or Missingness Mechanism
estimateQ

Initial Estimation of Q portion of the Likelihood