| basiSet.MAG | basiSet.MAG |
| CI.algorithm | The CI.algorithm function |
| DAG.to.MAG.in.pwSEM | Title DAG.to.MAG.in.pwSEM |
| generalized.covariance | Generalized covariance function |
| get.AIC | Title get.AIC |
| MAG.to.DAG.in.pwSEM | Title MAG.to.DAG.in.pwSEM |
| MCX2 | Title Monte Carlo chi-square (MCX2) |
| nested_data | nested_data: |
| perm.generalized.covariance | perm.generalized.covariance |
| pwSEM | The pwSEM function |
| sim_normal.no.nesting | sim_normal.no.nesting Simulated data with correlated errors involving endogenous variables, normally-distributed data and without any grouping structure Data generated using this mixed acyclic graph: X1->X2->X3->X4 and X2<->X4 |
| sim_normal.with.nesting | sim_normal.with.nesting: Simulated data with correlated errors involving endogenous variables, normally-distributed data and without any grouping structure Data generated using this mixed acyclic graph: X1->X2->X3->X4 and X2<->X4 |
| sim_poisson.no.nesting | sim_poisson.no.nesting: Simulated data with correlated errors involving endogenous variables, Poisson-distributed data and without any grouping structure Data generated using this mixed acyclic graph: X1->X2->X3->X4 and X2<->X4 |
| sim_tetrads | sim_tetrads: Simulated data to be used with the vanishing.tetrads function Data generated using this directed acyclic graph, with L being latent: L->X1, L->X2, L->X3->X4 |
| summary.pwSEM.class | Summary Method for pwSEM Class |
| vanishing.tetrads | The vanishing.tetrads function |
| view.paths | view.paths |