Modern Sequential Analysis and Its Applications to Computerized Adaptive Testing

After a brief review of recent advances in sequential analysis involving sequential generalized likelihood ratio tests, we discuss their use in psychometric testing and extend the asymptotic optimality theory of these sequential tests to the case of sequentially generated experiments, of particular...

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Bibliographic Details
Published in:Psychometrika 2008-09, Vol.73 (3), p.473-486
Main Authors: Bartroff, Jay, Finkelman, Matthew, Lai, Tze Leung
Format: Article
Language:English
Subjects:
Adaptive Testing
Assessment
Behavioral Science and Psychology
Biological and medical sciences
Computer Assisted Testing
Experiments
Fundamental and applied biological sciences. Psychology
Humanities
Hypotheses
Item response theory
Law
Mastery Tests
Psychology
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics
Psychometrics. Statistics. Methodology
Quantitative psychology
Sequential Approach
Statistical Analysis
Statistical Theory and Methods
Statistics for Social Sciences
Statistics. Mathematics
Test Items
Test Length
Testing
Testing and Evaluation
Theory and Methods
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Description
Summary:After a brief review of recent advances in sequential analysis involving sequential generalized likelihood ratio tests, we discuss their use in psychometric testing and extend the asymptotic optimality theory of these sequential tests to the case of sequentially generated experiments, of particular interest in computerized adaptive testing. We then show how these methods can be used to design adaptive mastery tests, which are asymptotically optimal and are also shown to provide substantial improvements over currently used sequential and fixed length tests.
ISSN:0033-3123
1860-0980
DOI:10.1007/s11336-007-9053-9