Multivariate Statistics and Methodology in R

Multivariate Statistics and Methodology in R (MSMR) is an advanced semester-long course designed for Masters students in psychology seeking a deeper understanding of statistical techniques to analyze complex data sets with multiple sources of variation. Building on the foundation laid by the Univariate Statistics and Methodology in R (USMR) course, MSMR extends students’ analytical repertoire to encompass multilevel models, Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM).

The initial half of the course introduces students to the intricacies of multilevel models, providing a solid theoretical framework for understanding hierarchical data structures. Students will gain practical insights into applying these models to address research questions involving nested data and varying sources of variation.

The second half of the course delves into methods such as PCA and EFA for reducing dimensionality of data, before moving to Confirmatory Factor models and subsequently Structural Equation Models as a means of modeling and testing our theories about psychological constructs.