The Quantitative Psychology concentration focuses on the quantitative and methodological issues in conducting psychological research. The quantitative issues are loosely categorized into application of statistical methods to psychological study, psychometrics, and mathematical modeling of psychological processes.
The Quantitative area provides statistical consultation to members of the department through the Statistical consulting committee. The Statistical consulting committee provides faculty and graduate students in the department with consultation on statistical issues in data analysis and research design. Currently, the committee consists of Ehri Ryu (Chair) and Hiram Brownell. Click here for more information.
Hiram Brownell’s research interests center on language and communication in adults. Most of his work examines the effects of brain injury on people's ability to produce and understand differ forms of language. Analysis of brain lesions and associated deficits can be used to build and test theories of normal cognition and can also be used to address real problems affecting patients and their families. Specific areas of interest include nonliteral language such as metaphor and sarcasm, treatment programs, discourse, humor, Theory of Mind, prosody, and lexical semantics.
Ehri Ryu’s research interests include a broad range of multivariate statistical methods used in psychological research. Her current research specializes in multilevel modeling and analysis of longitudinal data. In particular, she is interested in assessment of model fit multilevel structural equation modeling, and comparing two approaches to analyzing multivariate multilevel data: multilevel covariance structure analysis vs. multilevel structural equation modeling with random coefficients. She is also interested in analyzing longitudinal relationship between multiple variables.
Scott Slotnick evaluates models of memory. The widely accepted dual-process model assumes memory is based on either the all-or-none process of recollection or on the continuous process of familiarity, while the single-process signal detection model assumes memory is a continuous process. During memory for source/context, the dual-process model predicts a linear receiver operating characteristic (ROC, a plot of hit rates versus false alarms) while the signal detection model predicts a curved ROC. Prof. Slotnick and his colleagues have found evidence that source memory ROCs are curved which indicates memory is a continuous process.