Engineering Psychophysiology: Issues and Applications

By Richard W. Backs; Wolfram Boucsein | Go to book overview
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Chapter 3
The Design and Analysis of Experiments in Engineering Psychophysiology

Julian F. Thayer1 University of Missouri--Columbia National Institute of Aging

Bruce H. Friedman Virginia Polytechnic Institute and State University

Biobehavioral research is among the most challenging of scientific endeavors. The study of interactions between living systems and their environments has tested the limits of research methodologies and theoretical models. Research designs in engineering psychophysiology, as in most biobehavioral research, have been characterized by the use of single dependent variables (DV) or multiple DVs treated singly that are averaged over subjects and discrete experimental epochs on a single measurement occasion. Although these designs have provided a great deal of useful information, their origins in agronomy suggest that they may hold limited generalizability to the study of humans as complex living systems ( Ford & Ford, 1987). Importantly, in the context of engineering psychophysiology one often wants to make inferences about transactions between individual human beings and their environments. The typical research design oversimplifies the complexity of these relationships and thus does not unambiguously allow for such inferences. Rather, these designs tend to obscure underlying processes by shrouding rich individual data with group data aggregation procedures ( Glass & Mackey, 1988; O'Connor, 1990).

The contributions of the co-authors of this chapter were equal; order of authorship was arbitrary.


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