How I Perform Factor Analysis in R

How I Perform Factor Analysis in R

Factor analysis is a statistical method that can help us understand the underlying structure of a set of variables. It can reduce the complexity of data by finding a smaller number of latent factors that explain the variation in the observed variables. In this article, I will show you how I chose to perform factor analysis in R, using an example dataset and some useful packages and functions. Key Points It can identify the relationships among many variables and summarize them into a few factors representing common themes or dimensions. It can be divided into exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). EFA is used when there is no prior knowledge or hypothesis about the number or nature of the factors, while CFA is used when there is some theoretical or empirical basis for specifying the number and structure of the factors. It can be performed using different methods for extracting factors, such as principal component analysis (PCA), principal axis factoring (…