ml-nmr-methodologylisted

# ML-NMR Methodology Comprehensive methodological guidance for conducting rigorous Multilevel Network Meta-Regression following NICE DSU guidance and multinma package documentation. ## When to Use This Skill - Deciding whether ML-NMR is appropriate - Setting up integration points for AgD - Specifying priors and models - Understanding marginal vs conditional effects - Predicting to target populations - Reviewing ML-NMR code or results ## When to Use ML-NMR ### ML-NMR is Appropriate When: 1. **Network Structure** - Multiple treatments form (partial) network - Some studies have IPD, others only AgD - Want to leverage all available evidence 2. **Population Differences** - Effect modifiers differ across populations - Standard NMA transitivity violated - Need population-adjusted estimates 3. **Target Population** - Want predictions for specific population - Different from any single trial population - Policy-relevant population definition ### ML-NMR vs Alternatives | Scenario | Recommended Method | |----------|-------------------| | All AgD, similar populations | Standard NMA | | All AgD, different populations | NMA meta-regression | | IPD for one study, AgD for one | MAIC or STC | | IPD + AgD network | ML-NMR | | Disconnected with IPD | ML-NMR (with assumptions) | ## Key Concepts ### Individual-Level vs Study-Level ``` ML-NMR Models Both: ├── Individual-level (within IPD studies) │ - Patient-level outcomes │ - Patient-level covariates │