Factor Analysis and Related Methods (3 credits)
ASTAT 440

Description: In factor analysis, a factor is an unobservable construct hypothesized to give rise to observed variables (e.g., responses to questionnaire items). This course introduces popular factor-analytic models and methods for fitting them to data, in both exploratory and confirmatory contexts. Models for (approximately) continuous observed data are covered, as well as those for categorical observed data, including a few models and methods of item response theory. Application and interpretation are emphasized, with statistical theory introduced as needed. Use of one or more computer programs will be required (no experience with factor-analytic software is assumed).

Prerequisites: Introduction to Applied Statistics (or equivalent), and Intermediate Applied Statistics: Linear Models (or equivalent).