Aim:
This course is predominantly an applied statistical course. It aims to provide the basic theoretical and operational concepts to the student about multivariate statistical models and score-based multivariate regression commonly applied demography and economics. The following clustering methods will be covered: Grade of Membership and Latent Class Models. The following scoring methods will be covered: Cronbach’s alfa, Principal Components Analysis, and Exploratory Factor Analysis. The student will be introduced to principals of Structural Equation through Confirmatory Factor Analysis and Path Models. I expect that students read the suggested literature specific to each method, as well participate in the data laboratory classes. At the end of the course I expect students to be able to manipulate data in all programs used during the course (Stata, R, Latent Gold, GoM 3.4, ugom, gomRccp) and apply the methods to specific areas of interest in Demography, Economics, and Health Studies.
Tests and Grading:
- 50 points to an empirical application of any cluster method learned
- 50 points to an empirical application of any scoring or path method learned
More details:
Download the complete syllabus here. Download 
