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Authors: Susan Gruber, Mark van der Laan
Title: [download]
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tmle: An R Package for Targeted Maximum Likelihood Estimation
Reference: Vol. 51, Issue 13, Nov 2012
Submitted 2011-02-07, Accepted 2012-10-02
Type: Article
Abstract:

Targeted maximum likelihood estimation (TMLE) is a general approach for constructing an efficient double-robust semi-parametric substitution estimator of a causal effect parameter or statistical association measure. tmle is a recently developed R package that implements TMLE of the effect of a binary treatment at a single point in time on an outcome of interest, controlling for user supplied covariates, including an additive treatment effect, relative risk, odds ratio, and the controlled direct effect of a binary treatment controlling for a binary intermediate variable on the pathway from treatment to the out- come. Estimation of the parameters of a marginal structural model is also available. The package allows outcome data with missingness, and experimental units that contribute repeated records of the point-treatment data structure, thereby allowing the analysis of longitudinal data structures. Relevant factors of the likelihood may be modeled or fit data-adaptively according to user specifications, or passed in from an external estimation procedure. Effect estimates, variances, p values, and 95% confidence intervals are provided by the software.

Paper: [download]
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tmle: An R Package for Targeted Maximum Likelihood Estimation
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Supplements: [download]
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tmle_1.2.0-3.tar.gz: R source package
(application/x-gzip, 30.7 KB)
[download]
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v51i13.R: R example code from the paper
(application/octet-stream, 7.4 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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