Luque, MA. 2017. eltmle: Ensemble Learning Targeted Maximum Likelihood Estimation. [Online]. GitHub. Available from: https://github.com/migariane/meltmle
Luque, MA. eltmle: Ensemble Learning Targeted Maximum Likelihood Estimation. [Internet] LSHTM Data Compass. GitHub; 2017. Available from: https://github.com/migariane/meltmle
Luque, MA (2017). eltmle: Ensemble Learning Targeted Maximum Likelihood Estimation. [Data Collection]. GitHub. https://github.com/migariane/meltmle
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 (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 |
Depositor | Gareth Knight |
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Date Deposited | 07 Apr 2017 13:34 |
Last Modified | 01 Mar 2019 17:35 |
Publisher | GitHub |