Alcohol Expectancy Multi-Axial Assessment: A Memory Network-based Approach
Document Type
Article
Publication Date
3-2004
Keywords
expectancy assessment, alcohol expectancy research, developing memory theory, information processing network, multidimensional scaling, predictive models, multiaxial assessment, heuristic map
Digital Object Identifier (DOI)
http://doi.org/10.1037/1040-3590.16.1.4
Abstract
Despite several decades of activity, alcohol expectancy research has yet to merge measurement approaches with developing memory theory. This article offers an expectancy assessment approach built on a conceptualization of expectancy as an information processing network. The authors began with multidimensional scaling models of expectancy space, which served as heuristics to suggest confirmatory factor analytic dimensional models for entry into covariance structure predictive models. It is argued that this approach permits a relatively thorough assessment of the broad range of potential expectancy dimensions in a format that is very flexible in terms of instrument length and specificity versus breadth of focus.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Psychological Assessment, v. 16, no. 1, p. 4-15
Scholar Commons Citation
Goldman, Mark S. and Darkes, Jack, "Alcohol Expectancy Multi-Axial Assessment: A Memory Network-based Approach" (2004). Psychology Faculty Publications. 1391.
https://digitalcommons.usf.edu/psy_facpub/1391
