highest.mi: Identifies highest MI from list of MIs.

In gimme: Group Iterative Multiple Model Estimation

Identifies highest MI from list of MIs.

Description

Identifies highest MI from list of MIs.

Usage

highest.mi(
  mi_list,
  indices,
  elig_paths,
  prop_cutoff,
  n_subj,
  chisq_cutoff,
  allow.mult,
  ms_tol,
  hybrid,
  dir_prop_cutoff,
  rmsea_cutoff = 0.05,
  srmr_cutoff = 0.05,
  nnfi_cutoff = 0.95,
  cfi_cutoff = 0.95,
  n_excellent = 2
)

Arguments

mi_list	A list of MIs across individuals
indices	A list of fit indices. Only relevant at the individual-level.
elig_paths	A character vector containing eligible paths that gimme is allowed to add to a model (e.g., no nonsense paths).
prop_cutoff	The proportion of individuals for whom a path must be significant in order for it to be added to the models. NULL if used at the individual-level.
n_subj	The number of subjects in a given stage of the search. If in the group stage, n_subj equals the number of subjects. If in the subgroup stage, n_subj equals the number of individuals in a given subgroup. At the individual stage, n_subj = 1.
chisq_cutoff	Cutoff used in order for MI to be considered significant. Value varies depending on stage of search (e.g., group, subgroup, individual).
rmsea_cutoff	Cutoff for RMSEA for an individual model(default is .05; must be between 0.0 and 1.0).
srmr_cutoff	Cutoff for SRMR for an individual model (default is .05; must be between 0.0 and 1.0).
nnfi_cutoff	Cutoff for NNFI for an individual model (default is .95; must be between 0.0 and 1.0).
cfi_cutoff	Cutoff for CFI for an individual model (default is .95; must be between 0.0 and 1.0).
n_excellent	Number of fit indices needed to surpass their cutoffs for an individual model to be considered excellent. Default is 2. Max is 4.

Value

Returns name of parameter associated with highest MI. If no MI meets the criteria, returns NA.

gimme documentation built on Aug. 22, 2025, 5:13 p.m.