Introduction | Installation | A matching workflow with the lalonde data | Step 1: Estimate the model-averaged propensity score | Step 2: Match on the averaged propensity score | Step 3: Assess balance, including prognostic-score balance | Step 4: Estimate the treatment effect | Interpreting the output | print() | summary() | plot() | FAQ | Doesn't using the outcome bias my analysis? | References

Notation | The simplex grid and tie-breaking | Step 1: Candidate models | Step 2: $\gamma$ — the model-averaged prognostic score | Step 3: $\lambda$ — the model-averaged propensity score | criterion = "logloss" | criterion = "smd" | criterion = "ks" | criterion = "prog" (the default; the paper's "Prog (Ave)") | Vertex mode | Criterion vs. display conventions for the SMD denominator | Five documented fixes relative to the paper's reference code | Relation to other software | Limitations | References

Introduction | ATT weighting | The ecosystem route: psave_weight() | The direct route: weights() | The paper's estimator: survey::svyglm() | ATE weighting | Note on estimand-specific formulas | References

Introduction | Installation | A matching workflow with the lalonde data | Step 1: Estimate the model-averaged propensity score | Step 2: Match on the averaged propensity score | Step 3: Assess balance, including prognostic-score balance | Step 4: Estimate the treatment effect | Interpreting the output | print() | summary() | plot() | FAQ | Doesn't using the outcome bias my analysis? | References

Notation | The simplex grid and tie-breaking | Step 1: Candidate models | Step 2: $\gamma$ — the model-averaged prognostic score | Step 3: $\lambda$ — the model-averaged propensity score | criterion = "logloss" | criterion = "smd" | criterion = "ks" | criterion = "prog" (the default; the paper's "Prog (Ave)") | Vertex mode | Criterion vs. display conventions for the SMD denominator | Five documented fixes relative to the paper's reference code | Relation to other software | Limitations | References

Introduction | ATT weighting | The ecosystem route: psave_weight() | The direct route: weights() | The paper's estimator: survey::svyglm() | ATE weighting | Note on estimand-specific formulas | References