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Home Page: https://haziqj.ml/lavaan.bingof/
License: GNU General Public License v3.0
Limited Information Goodness of Fit Tests for Binary Factor Models
Home Page: https://haziqj.ml/lavaan.bingof/
License: GNU General Public License v3.0
The current bottleneck in the test statistics calculation is the call to lav_model_vcov
from the {lavaan}
package. It is more apparent when
lavaan.bingof/R/04-test_statistics.R
Lines 70 to 98 in a525c2b
profvis results
print()
can display the simulation settings.
summary()
would do something like the mean rejection rate. Needs input sig_level = 0.05
.
Need to also add the tests (that are commented out in the R files) as an article perhaps.
Some of the R code in R/ folder contains tests which are commented. Nice to convert these to unit tests.
Nice to see the path diagram for the factor models.
The Rao-Scott adjustment seems natural to use in the context of complex sampling. The problem is it requires a Choleski decomposition of
install.packages("Matrix")
library(Matrix)
# Create a non-positive definite matrix
A <- matrix(c(4, 2, 2, 2, 4, 2, 2, 2, 4), nrow = 3, ncol = 3)
# Find the nearest positive definite matrix
nearest_pd <- nearPD(A, corr = FALSE, do2eigen = TRUE, ensureSymmetry = TRUE)
# Perform Cholesky decomposition on the nearest positive definite matrix
L <- chol(nearest_pd$mat)
print(L)
MOJ (2008): Two strategies exist to compute the GOF tests. Choose
Our tests that satisfy criteria 1:
Our tests that satisfy criteria 2:
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