migariane/eltmle
eltmle is a Stata program implementing the targeted maximum likelihood estimation for the ATE for a binary or continuous 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.
Alternative Title
eltmle: Ensemble Learning Targeted Maximum Likelihood Estimation (Implementation for Stata software)
Keywords
Outcome regression analysis, Targeted maximum likelihood estimationItem Type | Dataset |
---|---|
Capture method | Other |
Date | 30 June 2025 |
Language(s) of written materials | English |
Creator(s) |
Luque-Fernandez, MA |
LSHTM Faculty/Department |
Faculty of Epidemiology and Population Health > Dept of Medical Statistics Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology Faculty of Public Health and Policy > Dept of Health Services Research and Policy |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Funders |
Project Funder Grant Number Funder URI |
Date Deposited | 07 Aug 2025 15:52 |
Last Modified | 07 Aug 2025 15:52 |
Publisher | Github |
Explore Further
- Dept of Medical Statistics
- Dept of Non-Communicable Disease Epidemiology
- Dept of Health Services Research and Policy
- Github (Online Data Resource)