Package index • modelbpp

Main Functions

model_set() gen_models(): BIC Posterior Probabilities of Neighboring Models

model_graph(): Generate a Graph of Models

Helpers

fit_many(): Fit a List of Models

get_add(): Models That Are Less Restricted

get_drop(): Models That Are More Restricted

min_prior(): Minimum Prior

identical_partables() is_partable() same_variables() get_partables() to_partables(): Helper Functions For partables-Class Objects

measurement_invariance_models(): Measurement Invariance Models

model_set_combined(): Two or More Hypothesized Models

Methods

print(<partables>): Print a partables-Class Object

print(<sem_outs>): Print an sem_outs-Class Object

print(<model_set>): Print a model_set-Class Object

plot(<model_graph>): Plot a Network of Models

c(<partables>) c(<model_set>) partables_drop(): Manipulate Parameter Tables

Datasets

Datasets used in examples.

dat_cfa: A Sample Dataset Based On a Confirmatory Factor Analysis Model (For Testing)

dat_path_model: A Sample Dataset Based on a Path Model (For Testing)

dat_path_model_p06: A Sample Dataset Based On a Complex Path Model (For Testing)

dat_sem: A Sample Dataset Based On a Structural Model (For Testing)

dat_serial_4: A Sample Dataset Based On a Serial Mediation Model (For Testing)

dat_serial_4_weak: A Sample Dataset Based On a Serial Mediation Model With Weak Paths (For Testing)