Information about the Quantitative Psychology Graduate Major
Quantitative psychology provides an opportunity for students to specialize in measurement, methodology and research design and analyses relevant to data in the social sciences. Psychology faculty currently includes Steven Reise (chair), Peter Bentler, Jennifer Krull, and Rajesh Nandy. Key areas of interest among the faculty are structural equation modeling, item response theory, multilevel modeling, and the analysis of fMRI data.
The quantitative major at UCLA Psychology is a highly individualized program providing ample opportunity for one-on-one interaction with faculty. Students concentrating in quantitative psychology 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 and analytic techniques in substantive research. Some students find it compatible to give equal attention to both these major aspects of the program. Students in the quantitative program are strongly encouraged to collaborate with faculty in substantive areas of psychology in addition to their quantitative training. These areas include but are not limited to couples analysis, longitudinal and diary data, health outcomes, and the biological underpinnings of psychopathology.
During the first year of graduate work, quantitative psychology students 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 quantitative coursework. Concentration in the quantitative area 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. In addition to coursework in the Psychology Department, quantitative psychology students often take quantitative courses in other departments, including Education, Statistics, and Biostatistics.
Quantitative psychology students with substantive interests in educational issues might consider an affiliation with the Advanced Quantitative Methods (AQM) program (2 or 4-year fellowship). The AQM program in quantitative methods is a joint program supervised by faculty in both psychology and education. Education faculty currently includes Noreen Webb, Mike Seltzer, Li Cai, and Felipe Martinez.
More Quantitative Psychology Information
- For a list of Required Courses please see Section 12 of the Psychology Handbook
- Current Course Descriptions