Introduction | Cross-validation with linear regression | General workflow | Define folds | Define fold function | Apply cross_validate | Cross-validation with random forests | Cross-validation with dependence: time series | Session Information | References

Background and motivation | Conditional density estimation by pooled hazards regression | Example: Conditional density estimation | Nonparametric inverse probability weighted estimation | Example: Nonparametric IPW estimation | References

Introduction | Data and Notation | Simulate Data | Estimating the Effects of Additive MTPs | Interlude: Ensemble Machine Learning with sl3 | Efficient Effect Estimates with Machine Learning | Estimating the Effects of Additive MTPs Under Two-Phase Sampling | Statistical Inference for One-step and TML Estimators | Advanced Usage: User-Specified Nuisance Regressions | References

Introduction | Biomarker Identification | Visualization of Results | Session Information

Introduction | Biomarker Identification | Visualization of Results | Session Information

Introduction | Data and Notation | Simulate Data | Methodology | Interlude: Constructing Optimal Stacked Regressions with sl3 | Targeted Estimation of Stochastic Interventions Effects | Statistical Inference for Targeted Maximum Likelihood Estimates | References

Introduction | Data and Notation | Simulate Data | Methodology | Defining a grid of counterfactual interventions | Interlude: Constructing Optimal Stacked Regressions with sl3 | Initializing vimshift through its tmle3_Spec | Targeted Estimation of Stochastic Interventions Effects | Inference with Marginal Structural Models | Directly Targeting the MSM Parameter $\beta$ | References