Exploratory Factor Analysis (EFA)

Abstract

Dr. Shonn Cheng recently conducted an R U Serious session for META Lab members via Teams, focusing on Exploratory Factor Analysis (EFA). The session introduced the concept of EFA, explaining its purpose in identifying the underlying structure of data and determining the number of factors. Participants explored key applications of EFA, particularly in psychology and social sciences, to understand how observed variables relate to latent factors. Dr. Cheng provided hands-on demonstrations in R, guiding participants through conducting factor analysis, interpreting factor loadings, and evaluating model fit. The session emphasized the importance of understanding the assumptions behind EFA and selecting the appropriate methods based on data characteristics, offering participants valuable insights for applying EFA in their research.

Shonn Cheng

Assistant Professor

My research interests include applying a variety of analytical methods to study motivation, expertise, and technology-enhanced training.