An international leader in applications and theory of psychological measurement, the Quantitative/Psychometric Methods Program brings together the talents of program and affiliated faculty. You can specialize in one or more areas of psychometrics, including multivariate methodology such as factor analysis, structural equation modeling, item response theory, computerized adaptive testing, multi-way data analysis, and nonparametric methods. Students are encouraged to conduct research with more than one faculty member over the course of their studies. Affiliated faculty interests include methodological and substantive problems in cognitive measurement (including the measurement of abilities, aptitude, and achievement), psychopathology, personality measurement, and the measurement of preferences.
Our PhD program will prepare you for research, teaching, and technical careers. You will learn research skills that will help you develop innovative solutions to problems in psychological measurement and the analysis of psychological change. Our program's broad perspective covers problems of translating psychological observations into numerical form by developing psychological measurement instruments and developing new methods for scaling psychological data, for investigating the reliability and validity of psychological data, and for analyzing psychometric data using a variety of modeling approaches. Our Ph.D. program also maintains a close collaboration with the UMN School of Statistics and many of our students acquire an M.S. in Statistics while enrolled in the program. The Quantitative/Psychometric Methods Program does not accept students for a terminal M.A.
In our admissions process, we look for quantitative interests and skills and for some preparation and understanding of basic methods, techniques, and approaches to psychological research. We do not require a mathematics major or minor for admission, but you should appreciate the usefulness of mathematical methods as a tool in psychology. Course work in calculus, linear algebra, and statistics are also helpful. We also favorably regard undergraduate training in symbolic logic, in the philosophy of science, in the study of tests and measurements, and in psychological research.
N657 Elliott Hall