sl3 - Pipelines for Machine Learning and Super Learning
A modern implementation of the Super Learner prediction algorithm, coupled with a general purpose framework for composing arbitrary pipelines for machine learning tasks.
Last updated 3 months ago
data-scienceensemble-learningensemble-modelmachine-learningmodel-selectionregressionstackingstatistics
9.82 score 99 stars 7 dependents 748 scriptstmle3 - The Extensible TMLE Framework
A general framework supporting the implementation of targeted maximum likelihood estimators (TMLEs) of a diverse range of statistical target parameters through a unified interface. The goal is that the exposed framework be as general as the mathematical framework upon which it draws.
Last updated 3 years ago
causal-inferencemachine-learningtargeted-learningvariable-importance
7.60 score 37 stars 5 dependents 286 scriptsrtemis - Machine Learning and Visualization
Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.
Last updated 6 days ago
data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization
7.05 score 142 stars 2 dependents 45 scriptstmle3shift - Targeted Learning of the Causal Effects of Stochastic Interventions
Targeted maximum likelihood estimation (TMLE) of population-level causal effects under stochastic treatment regimes and related nonparametric variable importance analyses. Tools are provided for TML estimation of the counterfactual mean under a stochastic intervention characterized as a modified treatment policy, such as treatment policies that shift the natural value of the exposure. The causal parameter and estimation were described in Díaz and van der Laan (2013) <doi:10.1111/j.1541-0420.2011.01685.x> and an improved estimation approach was given by Díaz and van der Laan (2018) <doi:10.1007/978-3-319-65304-4_14>.
Last updated 4 months ago
causal-inferencemachine-learningmarginal-structural-modelsstochastic-interventionstargeted-learningtreatment-effectsvariable-importance
5.33 score 17 stars 1 dependents 42 scriptsmedoutcon - Efficient Natural and Interventional Causal Mediation Analysis
Efficient estimators of interventional (in)direct effects in the presence of mediator-outcome confounding affected by exposure. The effects estimated allow for the impact of the exposure on the outcome through a direct path to be disentangled from that through mediators, even in the presence of intermediate confounders that complicate such a relationship. Currently supported are non-parametric efficient one-step and targeted minimum loss estimators based on the formulation of Díaz, Hejazi, Rudolph, and van der Laan (2020) <doi:10.1093/biomet/asaa085>. Support for efficient estimation of the natural (in)direct effects is also provided, appropriate for settings in which intermediate confounders are absent. The package also supports estimation of these effects when the mediators are measured using outcome-dependent two-phase sampling designs (e.g., case-cohort).
Last updated 11 months ago
causal-inferencecausal-machine-learninginverse-probability-weightsmachine-learningmediation-analysisstochastic-interventionstargeted-learningtreatment-effects
4.37 score 13 stars 18 scriptstmle3mopttx - Targeted Maximum Likelihood Estimation of the Mean under Optimal Individualized Treatment
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.
Last updated 2 years ago
categorical-treatmentcausal-inferenceheterogeneous-effectsmachine-learningoptimal-individualized-treatmenttargeted-learningvariable-importance
4.25 score 12 stars 1 dependents 49 scriptstlverse - Umbrella Package for Targeted Learning in R
This is an umbrella package analogous to tidyverse that loads all the component packages of the tlverse, a set of Targeted Learning packages. It also includes a few data
Last updated 3 years ago
3.74 score 33 stars 1 dependents 11 scriptsmedshift - Causal mediation analysis for stochastic interventions
Estimators of a parameter arising in the decomposition of the population intervention (in)direct effect of stochastic interventions in causal mediation analysis, including efficient one-step, targeted minimum loss (TML), re-weighting (IPW), and substitution estimators. The parameter estimated constitutes a part of each of the population intervention (in)direct effects. These estimators may be used in assessing population intervention (in)direct effects under stochastic treatment regimes, including incremental propensity score interventions and modified treatment policies. The methodology was first discussed by I Díaz and NS Hejazi (2020) <doi:10.1111/rssb.12362>.
Last updated 3 years ago
causal-inferenceinverse-probability-weightsmachine-learningmediation-analysisstochastic-interventionstargeted-learningtreatment-effects
3.69 score 9 stars 11 scriptstmle3mediate - Targeted Learning for Causal Mediation Analysis
Targeted maximum likelihood (TML) estimation of population-level causal effects in mediation analysis. The causal effects are defined by joint static or stochastic interventions applied to the exposure and the mediator. Targeted doubly robust estimators are provided for the classical natural direct and indirect effects, as well as the more recently developed population intervention direct and indirect effects.
Last updated 3 years ago
causal-inferencecausal-mediation-analysismachine-learningmediation-analysisstochastic-interventionstargeted-learningtreatment-effects
2.98 score 6 stars 16 scriptsrtemisbio - rtemis Bio-informatics
Bio-informatics utilities
Last updated 3 months ago
2.60 score 1 stars 1 scripts