
| Document Type: | Dissertation |
| Name: | Reagan Brown |
| Email address: | Reagan.Brown@wku.edu |
| URN: | |
| Title: | The Development of a Computer Adaptive Test Of the Five Factor Model of Personality: Applications and Extensions |
| Degree: | Doctor of Philosophy |
| Department: | Psychology |
| Committee Chair: | Robert J. Harvey |
| Chair's email: | HarveyRJ@vt.edu |
| Committee\ Members: | |
| Keywords: | computer adaptive testing, CAT, personality testing, faking detection, intentional response distortion |
| Date of defense: | June 20, 1997 |
| Availability: | Release the entire work for Virginia Tech access only.
After one year release worldwide only with written permission of the student and the advisory committee chair. |
Although not universally accepted, much of the field has converged upon the Five Factor Model (FFM) of personality as constituting a comprehensive taxonomy of normal personality functioning. A weakness common to all personality inventories is excessive length, which can result in examinee fatigue, and ultimately, poor data quality. Computer adaptive testing offers a solution to the test fatigue problem by administering only the items that are informative for that examinee on a given scale. A new test based upon the FFM of normal personality administered in a computer adaptive fashion was constructed. Reliability and validity evidence were obtained, with favorable results. New approaches to the detection of intentional response distortion were explored with mixed results including some promising findings in need of cross-validation. Response latencies were able to discriminate between honest and faking subjects, but the findings were unable to clarify the issue of whether faking is an easier or more laborious cognitive process than honest answering. New directions in computer adaptive personality testing research are proposed.
List of Attached Files | ||
| rdbdiss6.pdf | ||
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At the author's request, all materials (PDF files, images, etc.) associated with this ETD are accessible from the Virginia Tech network only. |
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