This package estimates the optimal individualized treatment rule for the categorical treatment using Super Learner (sl3). In order to avoid nested cross-validation, it uses split-specific estimates of Q and g to estimate the rule as described by Coyle et al. In addition, it provides the Targeted Maximum Likelihood estimates of the mean performance using CV-TMLE under such estimated rules. This is an adapter package for use with the tmle3 framework and the tlverse software ecosystem for Targeted Learning.
Package details |
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| Maintainer | |
| License | GPL-3 |
| Version | 1.0.0 |
| URL | https://tlverse.org/tmle3mopttx |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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