bmlm: Bayesian Multilevel Mediation Models for Stan

Matti Vuorre's bmlm package enables easy estimation of Bayesian multilevel mediation models. The underlying data likely contains variables for modeling mediation effects within hierarchical structures. The dataset is associated with a method for statistical analysis in fields like psychology and social science.

Use Cases

• Estimate indirect effects in psychological studies based on the multilevel mediation framework.
• Fit Bayesian hierarchical models for social science research based on the described statistical method.
• Conduct sensitivity analysis for mediation pathways based on the Bayesian probability approach.
• Test theoretical models with clustered or longitudinal data based on the multilevel model capability.

Strengths

• Implements a specialized Bayesian multilevel mediation method.
• Built on the Stan probabilistic programming language for reliable inference.

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

Matti Vuorre