MultilevelTools: Diagnostic Metrics for Multilevel and Mixed Effects Models

multilevelTools provides effect sizes, diagnostics, and performance metrics for multilevel and mixed effects models. The package includes marginal and conditional R² estimates for linear mixed effects models based on Johnson (2014). It was authored by Joshua F. Wiley.

Use Cases

• Calculate marginal and conditional R² for linear mixed effects models based on the cited methodology.
• Perform diagnostic checks on multilevel model performance using the provided metrics.
• Compute effect sizes for multilevel and mixed effects models to quantify predictor influence.

Strengths

• Implements a specific, cited methodology (Johnson, 2014) for R² estimation.
• Focuses on a specialized statistical domain (multilevel and mixed effects models).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Joshua F. Wiley