Quantitative

The program in quantitative psychology is a joint program supervised by faculty in both psychology and education. Psychology faculty currently includes Steven Reise (chair), Peter Bentler, Jennifer Krull, and Rajesh Nandy. Education faculty currently includes Noreen Webb, Mike Seltzer, and Bengt Muthen. Graduate students who have been admitted to either Psychology or Education may major in quantitative psychology, however, it is not possible to switch graduate programs (e.g., from education to psychology) once admitted. The interdisciplinary program in quantitative psychology at UCLA offers excellent opportunities for students with the aptitude and interest for this field. Students concentrating in this area will generally fit into one of two categories. The first of these consists of students possessing excellent mathematical backgrounds and strong theoretical interests in technical problems in measurement theory, statistics, and modeling. The second group of students typically has more applied interests. While the latter group of students have preparation in mathematics, these students are more oriented toward the use of psychometric techniques in substantive research in the areas of test development, experimental design, personality assessment, clinical measurement, and computer applications. Some students find it compatible to give equal attention to both these major aspects of the program.

Although the area offers the student a well-rounded education in the traditional content fields, it is a nationally recognized center for the development and application of latent variable modeling methods in particular. Most graduate students in the quantitative program emphasize either structural equation or item response theory modeling research.

During the first year of graduate work, the student will be exposed to a broad spectrum of courses covering the major fields of psychology. Some time during this year will also be devoted to research activities and coursework related to the major field. Concentration in the major field will be more intense during the second year. At a minimum, students are expected to take course work in traditional measurement, item response theory, latent variable modeling, multivariate analysis, and hierarchical linear modeling. Additional coursework such as classes on factor analysis, statistical analysis of fMRI data, and intervention design and analysis are strongly encouraged.