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Essential workflows for building and inspecting distributional piecewise SEMs.

Distributional piecewise SEM with drmSEM

drmSEM overview

Distributional Pathways

Propagate effects across location, scale, shape, and zero-inflation components.

Effect decomposition

Equations via symbolizer

Phylogenetic distributional SEM

Latents & Measurement

Incorporate formative, reflective, and MIMIC measurement constructs with reliability metrics.

Latent constructs and measurement models in drmSEM

Covariance edges, composites, and path attribution

Feedback & Covariance

Model reciprocal causation with Banach fixed-point equilibria and joint bivariate correlation.

Bivariate nodes: joint estimation, residual correlation, and moderation (drm_pair)

Feedback cycles: reciprocal causation and equilibrium effects (drm_cycle)

Missing Data & Diagnostics

Graph-derived piecewise imputation, model comparison, d-separation calibration, and recovery validation.

Graph-derived piecewise imputation for missing data (drm_sem)

Model selection with CBIC

drmSEM and other SEM tools

Calibrating the d-separation test

Effect-interval coverage and model-selection recovery