Quantitative psychology is the science of studying and developing methods and statistical models for the purposes of measuring and studying human behavior and other allied areas of study. The birth of quantitative psychology has been motivated by the need to solve problems in psychology with the application of applied mathematics overlapping with statistics. The traditional areas of quantitative research in our program include psychometrics (e.g., factor analysis and item response theory), mathematical psychology, and judgment and decision making. Contemporary research in quantitative psychology has expanded to include research design, mediation models, latent variable models, multilevel models, longitudinal data analysis, graphical analysis, Bayesian analysis, decision models, and other related methods.
Our quantitative program has a long and distinguished history. Numerous internationally prominent quantitative and mathematical psychologists have been on the faculty of Ohio State such as Robert C. MacCallum, Barbara Mellers, Elke Weber, Michael W. Browne, Jay Myung, Hal Arkes, and Robert C. Cudeck. A brief history of our program and the faculty who contributed to this narrative can be found here.
Many graduates of the quantitative psychology program have gone on to be highly successful in their academic and non-academic careers. Distinguished academics include Guangjian Zhang, Kristopher J. Preacher, Ed Merkle, Hao Wu, and Brandon Turner. Prominent non-academics are Tateneni Krishna, Longjuan Liang, and Xu Nu. A list of many of our graduates can be found here.
Areas of Emphasis
Traditionally, there are three main areas of emphasis in the quantitative program: psychometric methods, mathematical psychology, and aspects of judgment and decision making (JDM). Specific topics in psychometric methods include measurement, multivariate quantitative methods, such as factor analysis and covariance structure modeling, multilevel modeling and mixture analysis. Specific topics in mathematical psychology and JDM include axiomatic, algebraic, and stochastic modeling in such fields as decision making, judgment, and categorization.
More information regarding the graduate program in quantitative psychology can be found here. Prospective students interested in applying to our program should contact the program coordinator Trisha Van Zandt for more information.
News for Fall 2017