Factor (EFA and CFA) analysis in R

How to run EFA and CFA analysis in R

Here are the basic steps for running EFA and CFA in R using the psych and lavaan packages, respectively.

Exploratory Factor Analysis (EFA) using the psych package:

Sample EFA Output

Firstly, make sure you have the necessary packages installed. You can install them by running:

install.packages("psych")

install.packages("lavaan")

EFA Example:

# Load the required library library(psych)

# Example dataset (replace with your own dataset) data <- read.csv("your_data.csv")

# Run EFA efa_result <- fa(data, nfactors = 3, rotate = "varimax")  

# Change nfactors according to your analysis

# View the factor loadings print(efa_result$loadings)

Confirmatory Factor Analysis (CFA) using the lavaan package:

# Load the required library library(lavaan)

# Example dataset (replace with your own dataset) data <- read.csv("your_data.csv")

# Define the CFA model cfa_model <- ' # Define your model here using syntax from lavaan latent_variable =~ observed_item1 + observed_item2 + observed_item3 # Add more variables and relationships as needed '

# Fit the CFA model cfa_result <- lavaan::cfa(cfa_model, data = data, estimator = "ML")  

# Change estimator as needed

# Summarize the results summary(cfa_result, fit.measures = TRUE)