Examples | Numeric | Integers | Character | Factors | Logical | Matrices | Lists | data.frames | Using smd with dplyr | Other packages | References

Preliminaries | The Basic Approach | Example 4: Instrumental variables | Connections to the Influence Curve | Example 5: Hodges-Lehmann estimator | Non-smooth $\psi$ functions | Example 6: Huber center of symmetry estimator | Example 7: Sample quantiles (approximation of $\psi$) | Regression M-estimators | Example 8: Robust regression | Example 9: Generalized linear models | Application to test statistics | Example 10: Testing equality of success probabilities | References

Estimating a propensity score vs. treating propensity as known | IPW estimator of counterfactual mean | Doubly-Robust Estimator

JSS article | Using inferference | User's guide | The interference object | Utility functions | Example: Vaccine Study | Plotting effect estimates | Diagnostics | Example: Voting Experiment | Household-level propensity | Coding the propensity function | Evidence of a peer influence effect | Computational Issues with IPW Estimators | References

Choice of rootFUN | Building a custom root finder

Introduction | Corrections included with geex | Bias correction example | Comparision to saws package | References

From M-estimation math to code | Calculus of M-estimation Examples | Example 1: Sample moments | Example 2: Ratio estimator | Example 3: Delta method continued | References

The Estimating Function | M-estimation basis | Finding roots | Computing the Empirical Sandwich Variance Estimator | M-estimation with m_estimate

Motivation | Data | Estimating equations | Computation time | Results comparison

Direct Effects | Indirect Effects