Multiple Correspondence Analysis (MCA) in Educational Data
AUTHOR AFFILIATION Nirmal Ghimire, Ph.D. K-16 Literacy Center at University of Texas at Tyler PUBLISHED May 19, 2023 Introduction Multiple Correspondence Analysis (MCA) is a multivariate statistical technique that is used to analyze the relationships between categorical variables. It is a generalization of correspondence analysis (CA), which is used to analyze the relationships between two categorical variables. MCA can be used to explore the associations between multiple categorical variables simultaneously. MCA works by creating a map of the categorical variables. The map is created by calculating the distances between the different categories of the variables. The closer two categories are on the map, the more similar they are. The further apart two categories are on the map, the less similar they are. MCA can be used to explore a variety of research questions. For example, MCA can be used to: Explore the relationships between different demographic variables, such as age, gender