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ERIC Number: EJ809792
Record Type: Journal
Publication Date: 2008-Jul
Pages: 21
Abstractor: As Provided
Reference Count: 32
ISSN: ISSN-0027-3171
Item Selection for the Development of Short Forms of Scales Using an Ant Colony Optimization Algorithm
Leite, Walter L.; Huang, I-Chan; Marcoulides, George A.
Multivariate Behavioral Research, v43 n3 p411-431 Jul 2008
This article presents the use of an ant colony optimization (ACO) algorithm for the development of short forms of scales. An example 22-item short form is developed for the Diabetes-39 scale, a quality-of-life scale for diabetes patients, using a sample of 265 diabetes patients. A simulation study comparing the performance of the ACO algorithm and traditionally used methods of item selection is also presented. It is shown that the ACO algorithm outperforms the largest factor loadings and maximum test information item selection methods. The results demonstrate the capabilities of using ACO for creating short-form scales. (Contains 4 tables, 5 figures and 1 footnote.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A