Luque, MA. 2017. migariane/meltmle: Ensemble Learning Targeted Maximum Likelihood Estimation for Stata users. [Online]. Zenodo. Available from: https://doi.org/10.5281/zenodo.2560827
Luque, MA. migariane/meltmle: Ensemble Learning Targeted Maximum Likelihood Estimation for Stata users [Internet]. Zenodo; 2017. Available from: https://doi.org/10.5281/zenodo.2560827
Luque, MA (2017). migariane/meltmle: Ensemble Learning Targeted Maximum Likelihood Estimation for Stata users. [Data Collection]. Zenodo. https://doi.org/10.5281/zenodo.2560827
Description
eltmle is a Stata program implementing the targeted maximum likelihood estimation for the ATE for a binary outcome and binary treatment. Future implementations will offer more general settings. eltmle includes the use of a "Super Learner" called from the SuperLearner package v.2.0-21 (Polley E., et al. 2011). The Super-Learner uses V-fold cross-validation (10-fold by default) to assess the performance of prediction regarding the potential outcomes and the propensity score as weighted averages of a set of machine learning algorithms. We used the default SuperLearner algorithms implemented in the base installation of the tmle-R package v.1.2.0-5 (Susan G. and Van der Laan M., 2017), which included the following: i) stepwise selection, ii) generalized linear modeling (glm), iii) a glm variant that included second order polynomials and two-by-two interactions of the main terms included in the model.
Keywords
Data capture method | Simulation |
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Date (Date published in a 3rd party system) | 9 March 2017 |
Language(s) of written materials | English |
Data Creators | Luque, MA |
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LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 07 Apr 2017 13:34 |
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Last Modified | 28 Sep 2021 13:10 |
Publisher | Zenodo |