title: Alcohol expectancy multiaxial assessment: a memory network-based approach.
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.
authors.affiliation: Department of Psychology, University of South Florida, Tampa, FL 33620-8200, USA. goldman@cas.usf.edu
authors.forename: Mark S
authors.initials: MS
authors.lastname: Goldman
authors.forename: Jack
authors.initials: J
authors.lastname: Darkes
mesh_terms: D000293:Adolescent; D000328:Adult; D000428:Alcohol Drinking / Q000523:psychology*; D000435:Alcoholic Intoxication / Q000523:psychology*; D003210:Concept Formation; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D011939:Mental Recall; D015233:Models, Statistical; D010552:Personality Assessment / Q000706:statistics & numerical data*; D011582:Psychological Theory; D011594:Psychometrics / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D012718:Set, Psychology; D013334:Students / Q000523:psychology