ggmFit example

# Needed packages:
library("qgraph")
library("psych")
library("huge")
data(bfi)

# Subset of 2000 to train model on:
bfiTrain <- huge.npn(bfi[1:1000,1:25])
corMat_train <- cor_auto(bfiTrain, missing = "fiml", detectOrdinal = FALSE)

# Rest to evaluate model:
bfiTest <- huge.npn(bfi[-(1:1000),1:25])
corMat_test <- cor_auto(bfiTest, missing = "fiml", detectOrdinal = FALSE)

# Fit network:
net <- ggmModSelect(corMat_train,nrow(bfiTrain))

# Fit measures in training set (refit not needed):
fit_train <- ggmFit(pcor = net$graph, sampleSize = nrow(bfiTrain), covMat = corMat_train, refit = FALSE)
fit_train$fitMeasures$network <- "train"

# Fit measures in test set (not refitting parameters):
fit_test_noRefit <- ggmFit(pcor = net$graph, sampleSize = nrow(bfiTest), covMat = corMat_test, refit = FALSE)
fit_test_noRefit$fitMeasures$network <- "test (no refit)"

# Fit measures in test set (also refitting each edge):
fit_test_refit <- ggmFit(pcor = net$graph, sampleSize = nrow(bfiTest), covMat = corMat_test, refit = TRUE)
fit_test_refit$fitMeasures$network <- "test (refit)"

# Display them all:
rbind(as.data.frame(fit_train$fitMeasures),
      as.data.frame(fit_test_noRefit$fitMeasures),
      as.data.frame(fit_test_refit$fitMeasures))[,c("network","rmsea","cfi","nfi")]