Dynamic Fit Index Cutoffs for Network Models

The goal of netDFI is to compute dynamic fit index (DFI) cutoffs for network models.

The reference of DFI for Gaussian graphical models: https://osf.io/preprints/psyarxiv/5wj2y_v1

Installation

You can install the development version of netDFI from GitHub with:

# install.packages("devtools")
# devtools::install_github("xinkaidupsy/netDFI")
install.packages("netDFI", repos = c('https://xinkaidupsy.r-universe.dev', 'https://cloud.r-project.org'))

Example

This is a basic example which shows you how to solve a common problem:

library(psych)
library(psychonetrics)
library(dplyr)
library(netDFI)

# get the big five inventory data from psych
data(bfi)

# estimate ggm 
bfi_mod <- ggm(bfi) %>% prune %>% runmodel     

# obtain the partial correlation matrix
bfi_net <- getmatrix(bfi_mod, "omega")

# allow future_apply to use more memory
options(future.globals.maxSize = 2 * 1024^3)

# run dfi
dfi_bfi <- dfi_ggm(
  bfi_net, 
  ncores = 1, 
  specificity = 0.80, 
  iter = 200,
  n_misspec = 2
)
dfi_bfi

# plot results
p <- plot(dfi_bfi)
p[[1]]