Quantitative Modeling in Behavioral Analysis, Part 2: How?
|Monday, May 30, 2016
|5:00 PM–5:50 PM
|Area: SCI; Domain: Basic Research
|Instruction Level: Basic
|CE Instructor: Blake A. Hutsell, Ph.D.
|Chair: Federico Sanabria (Arizona State University)
|BLAKE A. HUTSELL (Virginia Commonwealth University)
|Blake Hutsell received his doctoral training in experimental psychology at Southern Illinois University under the direction of Dr. Eric Jacobs. Subsequently he completed a postdoctoral fellowship at Auburn University under the direction of Dr. Chris Newland and currently holds a postdoctoral position in the Virginia Commonwealth University School of Medicine under the direction of Dr. Matt Banks. He was the 2011 recipient of the APA Division 25 Basic Behavior Analysis Dissertation Award and his publications have appeared in the Journal of the Experimental Analysis of Behavior, Neurobiology of Learning and Memory, Drug and Alcohol Dependence and other journals. His research interests include novel applications of quantitative models to socially-relevant behavioral phenomena such as drug addiction and neurotoxicant exposure to target underlying behavioral mechanisms that mediate these phenomena.
While quantitative modeling has become increasingly common in the behavior analytic literature, many researchers have received little formal training in the practical implementation of these methods. The purpose of this presentation is to encourage quantitative analyses of behavior by providing an introduction to modeling in Microsoft Office Excel. Excel represents an advantageous platform due to its wide availability to researchers in various settings and relative ease with which prominent quantitative models may be implemented. This presentation has three major aims: (1)to provide an overview of how to simulate quantitative models commonly encountered in the literature for the purposes of gaining an understanding of the model's behavior; (2) demonstrate how to set up a workbook to perform regression analyses and basic visual analyses to assess the goodness of a model's fit to data; (3) provide an accessible introduction to model selection techniques comparing nested and non-nested models to aid the identification of candidate behavioral mechanisms.
Licensed pschologists and those interested in quantitative modeling.
|Learning Objectives: At the conclusion of the presentation, the participant will be able to: (1) set up workbooks for model simulation and visualization to understand model behavior; (2) perform regression and implement model selections techniques.