|Component Analysis in Applied Behavior Analysis: Current Research and Future Directions
|Monday, May 30, 2022
|8:00 AM–8:50 AM
|Meeting Level 2; Room 203
|Area: TBA/EDC; Domain: Applied Research
|CE Instructor: Salvador Ruiz, Ph.D.
|Chair: JUSTIN N COY (University of Pittsburgh)
|SALVADOR RUIZ (University of West Florida)
|PETER STURMEY (The Graduate Center and Queens College, City University of New York)
|JOHN CLAUDE WARD-HORNER (Evergreen Center)
Component Analysis is a systematic approach to identify the effects of individual elements of a treatment package. Component Analysis serves two important roles for practitioners. First, it verifies to what extent each component of the package impacts behavior. It is important to recognize the degree of effectiveness to provide best practice treatment options. Second, allows for experimenters to select the most effective components of a treatment package (Riden et al., 2020). Two previous literature reviews identified studies that implemented component analysis and examined the degree of individual components' effects on behavior across studies (Riden et al., 2020; Ward-Horner & Sturmey, 2010). While those seeking to implement a component analysis review the literature, it appears that in many scenarios they are underutilized in SCRD. While many consider the value in understanding the effects of individual components, practitioners and students should be able to seek resources that examine the effects of treatments on behavior. Future literature reviews should examine the use of component analysis across participants and specialties to determine its frequency of appearance and use cases.
|Instruction Level: Intermediate
Attendees should have knowledge of: What a component analysis is How to determine if a component was evaluated in a graph
|Learning Objectives: 1. Identify a component analysis in the literature base 2. Establish visual inspection criteria for examining component effects 3. Locate research that utilizes component analysis in their study
|Keyword(s): Component Analysis, Experimental Design