Chi-Square Equivalence Test for Structural Equation Models.

Function that performs a chi-square equivalence test for structural equation models.

Usage

equiv_chi(alpha = 0.05, chi, df, m, N_sample, popRMSEA = 0.08)

Arguments

alpha

Value of the significance level, which is set to .05 by default.

chi

Value of the observed chi-square test statistic.

df

Number of model (or model difference in) degrees of freedom.

m

Number of groups.

N_sample

Sample size.

popRMSEA

The value of the root-mean square error of approximation (RMSEA) to set for the equivalence bounds, which is set to .08 by default.

Value

p-value indicating whether to reject the null hypothesis that the model is a poor fit to the data.

Details

Created by Counsell et al. (2020): Counsell, A., Cribbie, R. A., & Flora, D. B. (2020). Evaluating equivalence testing methods for measurement invariance. Multivariate Behavioral Research, 55(2), 312-328. https://doi.org/10.1080/00273171.2019.1633617

See also

Other structural equation modeling: make_esem_model(), puc(), satorraBentlerScaledChiSquareDifferenceTestStatistic(), semPlotInteraction()

Examples

# Prepare Data
data("mtcars")

# Fit structural equation model

# Extract statistics
N1 <- 1222
m <- 1
Tml1 <- 408.793
df1 <- 80

# Equivalence test
equiv_chi(alpha = .05, chi = Tml1, df = df1, m = 1, N_sample = N1, popRMSEA = .08)
#>       chi       Fml popep popdelt         pval
#> 1 408.793 0.3348018 0.512 625.152 3.091085e-11