Exploratory Factor Analysis
Learning Objectives
Upon completion of this comprehensive and engaging course, you will be able to:
- Explain the 5 core goals of Exploratory Factor Analysis (EFA)
- Conduct an EFA using SPSS
- Use eigenvalues, Cattell’s scree plots, and Horn’s parallel analysis to determine the number of factors underlying a construct
- List the recommended cutoff thresholds for key model fit statistics (incl. chi-square, RMSEA, TLI, and BIC)
- Conduct orthogonal (VARIMAX) as well as oblique (PROMAX) factor rotations
- Define, calculate, and interpret communalities
- Construct a path diagram
- List the assumptions underlying EFA
- Review sample size guidelines for EFA
Instructor
Christian Geiser, PhD is a former Professor of Quantitative Psychology with expertise in structural equation modeling, longitudinal data analysis, latent class modeling, multitrait-multimethod analysis, and psychometric methods. Dr. Geiser completed his doctoral training in quantitative psychology from Freie Universität Berlin in Germany, after which time he served as a faculty member at both Arizona State University as well as Utah State University, where he served as Principal Investigator on grants funded by the National Institutes of Health (NIH). In his academic career, he has published 75 peer-reviewed journal articles, 15 book chapters, and 5 books from leading publish houses such as Springer and Guilford Press. His work has been cited over 7,000 times, and he currently serves as an Editorial Board Member on Journal of Personality. Dr. Geiser provides statistical consultation services and serves as Director of Education for Quantfish, an online statistics training platform for health and social scientists.
