The project will investigate two distinct but related questions in psychological research. The first concerns response time (RT), the time taken to complete an experimental task. The shape of the RT distribution serves as a key marker of cognitive processing. Research will develop statistical methodology for testing whether shape is invariant or depends on covariates such as participant characteristics and experimental manipulations. The approach will be to choose appropriate distributions from a large class of three parameter distributions derived from the two-parameter exponential families introduced by Bar-Lev and Reiser augmented with a shift parameter. A unified approach will develop objective Bayesian methodology for this class of nonregular distributions. The second key research question is about the association of latent mental processes across people, items, and conditions. Understanding how these processes are related will provide insight into understanding cognition. The specific problem is to model the association of covariance matrices of two or more related bivariate distributions in a hierarchical setting. The project will develop objective priors for Bayesian analysis of these covariance matrices, generalizing recent developments in univariate signal-to-noise ratio priors.

Both phases of the project address fundamental and significant questions in cognitive research in psychology, with potential impact in related areas as well. The study of response times also is fundamental to research in developmental and social psychology as well as psychopathology. A number of theories have been developed for cognitive processing in these fields and how it is affected by experimental conditions and characteristics of the participant. Most of these theories predict shape changes in the distribution of response times. However, the fundamental question of whether or not the shape of these distributions actually changes as a response to experimental condition has not been studied. Understanding if and how response time distribution shape changes will spur new theoretical directions. In addition, useful new statistical methods will be developed applicable beyond psychology. The second problem, estimating covariance matrices of latent variables, is motivated by the study of different modes of recall in memory tasks. Participants given lists of words to study and subsequently queried on these words may respond because of an "automatic" response, based perhaps on previous familiarity, or they may respond based on actual recollection. Assessment of these two processes is complicated by the fact that some words may be simultaneously easier to recall automatically or easier to remember; similarly, people may tend to be better simultaneously at automatic response or recollection. Assessment of these relationships is delicate and challenging. The research will have impact on the psychological study of working memory and cognitive aging. In addition, the statistical models are closely related to those used in areas such as epidemiology, economics, and ecology. Thus the results of the project will have impact well beyond the psychological sciences.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Application #
0720229
Program Officer
Cheryl L. Eavey
Project Start
Project End
Budget Start
2007-09-15
Budget End
2010-08-31
Support Year
Fiscal Year
2007
Total Cost
$290,000
Indirect Cost
Name
University of Missouri-Columbia
Department
Type
DUNS #
City
Columbia
State
MO
Country
United States
Zip Code
65211