swMATH ID: 18463
Software Authors: Susan Gruber, Mark van der Laan
Description: R package tmle. Targeted Maximum Likelihood Estimation. Targeted maximum likelihood estimation of point treatment effects (Targeted Maximum Likelihood Learning, The International Journal of biostatistics, 2(1), 2006. This version adds the tmleMSM() function to the package, for estimating the parameters of a marginal structural model for a binary point treatment effect. 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. Effect estimation stratified by a binary mediating variable is also available. The population mean is calculated when there is missingness, and no variation in the treatment assignment. 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.
Homepage: https://cran.r-project.org/web/packages/tmle/index.html
Source Code: https://github.com/cran/tmle
Dependencies: R
Keywords: CRAN; R package; Targeted Maximum Likelihood Estimation; TMLE
Related Software: SuperLearner; R; gam; ltmle; caret; simcausal; arm; glmnet; BART; drtmle; EValue; episensr; optmatch; Matching; MatchIt; sbw; optweight; PSW; causalweight; CBPS
Cited in: 6 Publications

Standard Articles

1 Publication describing the Software Year

Citations by Year