Semiparametric inference for relative heterogeneous vaccine efficacy between strains in observational case-only studies
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Updated
Mar 25, 2023 - R
Semiparametric inference for relative heterogeneous vaccine efficacy between strains in observational case-only studies
Poster "Semiparametric estimation and robust empirical Bayes inference in high-dimensional biological studies" for the annual conference of the Superfund Research Program, November 2019
npRR: Model-robust inference for the conditional relative risk function using targeted machine learning
💬 Talk on causal inference and variable importance with stochastic interventions under two-phase sampling
💬 Talk on mediation effects based on stochastic interventions
An R Package for Average Causal Effect Estimation via the Front-Door Functional
🎯🎓 An introductory workshop lecture on a generalized framework for Targeted Learning using the tmle3 R package
Data-adaptive creation of exposure (treatment) mixtures using targeted learning
Quarto version of "Introduction to Modern Causal Inference" by Alejandro Schuler.
📦 🔬 R/methyvim: Targeted, Robust, and Model-free Differential Methylation Analysis
Implementing experiments in paper titled "Targeted Machine Learning for Average Causal Effect Estimation Using the Front-Door Functional"
🎯 🔀 Targeted Learning for Causal Mediation Analysis
Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
In this repository, we implement Targeted Meta-Learning (or Targeted Data-driven Regularization) architecture for training machine learning models with biased data.
🎯 🎲 Targeted Learning of the Causal Effects of Stochastic Interventions
💫 🎯 Automatic identification of variable and interaction importance using basis functions and non-parametric estimation of interactions/effect modification using joint stochastic interventions.
Course website for "Targeted Learning in Biomedical Big Data" (Spring 2018, UC Berkeley)
SuperLearner R package: prediction model ensembling method
A pure Julia implementation of the Targeted Minimum Loss-based Estimation
🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation
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