Date of Graduation
8-2024
Document Type
Thesis
Degree Name
Master of Science in Agricultural Economics (MS)
Degree Level
Graduate
Department
Agricultural Economics and Agribusiness
Advisor/Mentor
McFadden, Brandon
Committee Member
Nalley, Lanier L.
Second Committee Member
Cifranič, Michal
Keywords
Intentions; Likert scale; Validity
Abstract
It is common for researchers to ask participants to associate probabilities with words, often using tools like the Likert scale to measure behavioral intentions and attitudes. However, it remains unclear what specific probabilities participants assign to the response options on a Likert scale, how much variation exists across these options, and whether these probabilities differ across various behaviors. The purpose of this paper is to explore the numeric probabilities that participants associate with different Likert scale points, to understand their perception of the variation at each point, and to compare these perceptions across three behaviors: eating more vegetables, exercising more, and taking a risk. The findings of this study will provide valuable insights for future research using Likert scale response options. Our results reveal that participants perceive the Likert scale as more condensed than researchers typically assume. Rather than ranging from 0 to 100, participants' perceived probabilities span from approximately 22 to 86. Furthermore, the variation across response points increases as the likelihood increases, indicating that participants are more certain when they answer, "extremely unlikely" compared to "extremely likely." Finally, only minor differences were observed across the three behaviors studied, which will be discussed in more detail in the results section of this paper.
Citation
Schlichtig, E. (2024). Measurement Reliability for Intentions to Change Behavior. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5409
Included in
Agricultural Economics Commons, Behavioral Economics Commons, Econometrics Commons, Research Methods in Life Sciences Commons