A comparison between traditional economical and demand curve analyses of relative reinforcer efficacy in the validation of preference assessment predictions

Objective: This single-case study examined the degree to which three formal preference assessments (i.e. paired-stimulus, multiple-stimulus without replacement and a free-operant procedure) successfully identified reinforcers from six edibles in a subsequent reinforcement assessment. Methods: Econom...

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Bibliographic Details
Published in:Developmental neurorehabilitation 2009-01, Vol.12 (3), p.164-169
Main Authors: Reed, Derek D., Luiselli, James K., Magnuson, Jennifer D., Fillers, Stefanie, Vieira, Shawn, Rue, Hanna C.
Format: Article
Language:English
Subjects:
Autistic Disorder - psychology
behavioral economics
Choice Behavior
Decision Making
Demand curve
Humans
Male
Neuropsychological Tests
perference assessment
Photic Stimulation - methods
progressive ratio
Psychomotor Performance
Reinforcement (Psychology)
reinforcer assessment
Validation Studies as Topic
Young Adult
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Summary:Objective: This single-case study examined the degree to which three formal preference assessments (i.e. paired-stimulus, multiple-stimulus without replacement and a free-operant procedure) successfully identified reinforcers from six edibles in a subsequent reinforcement assessment. Methods: Economical analyses were conducted on the entire hierarchy of low-, moderate- and high-preferred edibles using both traditional (i.e. progressive-ratio breakpoint) and demand curve (Pmax) accounts of reinforcer efficacy with the data obtained from three reinforcement assessment sessions for each edible. Results: Across all three preference assessment types, accuracy in the identification of the top three reinforcers was 67%. The correlation between the traditional and demand curve metrics was highly significant, replicating previous research on the substitutability of these analyses. Conclusions: Moderate-preferred stimuli may serve as efficacious reinforcers in subsequent reinforcer assessments. Additionally, demand curve analyses can contribute to the assessment of reinforcer efficacy and subsequently the validation of preference assessments.
ISSN:1751-8423
1751-8431
DOI:10.1080/17518420902858983