# Installation check and installation of required packages for CFA and EGA
if (!require("psych")) install.packages("psych")  
if (!require("lavaan")) install.packages("lavaan")  
if (!require("qgraph")) install.packages("qgraph")  
if (!require("semPlot")) install.packages("semPlot")  

# Load libraries
library(psych)  
library(lavaan)  
library(qgraph)  
library(semPlot)  

# Define the model for Confirmatory Factor Analysis (CFA)
modelo_afc <- '
F1 =~ Q2 + Q3 + Q6 + Q7  # Define first factor with items Q2, Q3, Q6, Q7
F2 =~ Q4 + Q5 + Q8       # Define second factor with items Q4, Q5, Q8
'

# Fit the CFA model using the loaded dataset
ajuste_afc <- cfa(modelo_afc, data=Dataset_ajustado)

# Summary of the CFA results, including fit measures
summary(ajuste_afc, fit.measures=TRUE)  # Provides a detailed summary including fit indices

# Perform Exploratory Graph Analysis (EGA) with selected data
# Select and adjust based on the columns present in your dataset
cor_matrix <- cor(Dataset_ajustado[,c("Q2", "Q3", "Q6", "Q7", "Q4", "Q5", "Q8")], use="complete.obs")  
ega <- qgraph(cor_matrix, graph="cor", layout="spring")  

# Generate and visualize the Path Diagram of the CFA model using semPlot
path_diagram <- semPaths(ajuste_afc, whatLabels="std", layout="tree", rotation=2)