epcEquivCheck: EPC Equivalence Feasibility Check for Standardized Parameters

Description

Performs an EPC-based feasibility check to assess whether a set of standardized population parameters defines a valid population covariance matrix and whether trivially misspecified parameters remain within a user-defined smallest effect size of interest (SESOI). Feasibility is evaluated by constructing implied population models under targeted parameter perturbations and examining EPC behavior using epcEquivFit.

Usage

epcEquivCheck(lavaanObj, minRelEffect = 0.75, stdLoad = 0.4, cor = 0.1,
  corLatent = NULL, corResidual = NULL, stdBeta = 0.1)

Value

An object of class "epcEquivCheckStd" containing:

feasible: Logical indicator of whether a valid standardized population model exists.
any_M: Logical indicator of whether any EPC exceeded the SESOI under the evaluated misspecifications.
recommendation: Character string summarizing feasibility (e.g., "RECOMMENDED", "NOT RECOMMENDED").
M_table: Data frame summarizing EPCs exceeding the SESOI, if any.
testeffect: Data frame reporting the smallest tested standardized perturbations in each direction.

Arguments

lavaanObj: A fitted lavaan object representing the target model.
minRelEffect: A scalar in (0, 1) specifying the minimum relative magnitude of the standardized perturbation to be evaluated. The default value of 0.75 indicates that perturbations equal to 75\ the SESOI are treated as trivial. If EPCs exceed the SESOI under such perturbations, EPC equivalence testing is not recommended.
stdLoad: Standardized factor loading used to define the SESOI for loading misspecifications.
cor: Standardized correlation used as a default SESOI for covariance misspecifications. This value is used for both latent and residual covariances unless overridden by corLatent or corResidual.
corLatent: Standardized latent factor correlation used to define the SESOI for latent covariance misspecifications. If NULL, defaults to cor.
corResidual: Standardized residual correlation used to define the SESOI for indicator residual covariance misspecifications. If NULL, defaults to cor.
stdBeta: Standardized regression coefficient used to define the SESOI for structural misspecifications.

Details

This function focuses on standardized parameters and supports recursive SEMs with continuous indicators only.

The procedure first checks whether the standardized parameters imply a positive definite population covariance matrix. It then evaluates EPC behavior under both positive and negative trivial misspecifications by repeatedly constructing implied population covariance matrices with perturbed parameters (minRelEffect \(\times\) SESOI), refitting the model, and re-evaluating EPCs.

Models with categorical indicators, formative indicators, or multiple-group structures are not supported.

Examples

Run this code


library(lavaan)

one.model <- ' onefactor  =~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 '
fit <- cfa(one.model, data = HolzingerSwineford1939)
# \donttest{
epcEquivCheck(fit)
# }