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Multicomponent Latent Trait Models for Ability Tests

Published online by Cambridge University Press:  01 January 2025

Susan E. Whitely
Susan E. Whitely*
Affiliation:
University of Kansas
*
Requests for reprints should be sent to Susan E. Whitely, Psychology Department, University of Kansas, Lawrence, Kansas 66045.
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Abstract

A major research direction for ability measurement has been to identify the information-processes that are involved in solving test items through mathematical modeling of item difficulty. However, this research has had limited impact on ability measurement, since person parameters are not included in the process models. The current paper presents some multicomponent latent trait models for reproducing test performance from both item and person parameters on processing components. Components are identified from item subtasks, in which performance is a logistic function (i.e., Rasch model) of person and item parameters, and then are combined according to a mathematical model of processing on the composite item.

Keywords

latent trait modelsinformation-processing modelsability measurement

Information

Type
Original Paper
Information
Psychometrika , Volume 45 , Issue 4 , December 1980 , pp. 479 - 494
Copyright
Copyright © 1980 The Psychometric Society

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Footnotes

The author would like to thank David Thissen for his invaluable insights concerning this model and an anonymous reviewer for his suggestion about the sample space for the model.

This research was partially supported by National Institute of Education grant number NIE-6-7-0156 to Susan E. Whitely, principal investigator. However the opinions expressed herein do not necessarily reflect the position or policy of the National Institute of Education, and no official endorsement by the National Institute of Education should be referred. Part of this paper was presented at the annual meeting of the Psychometric Society, Monterey, California: June, 1979.

References

Reference Notes

Whitely, S. E. & Schneider, L. Process outcome models for verbal aptitude, 1980, Lawrence, Kansas: Department of Psychology, University of Kansas.Google Scholar
Frederiksen, J. R. A chronometric study of component skills in reading (NR 154–386 ONR Tech. Rep. 2), 1978, Cambridge, MA: Bolt, Beranek & Newman.Google Scholar

References

Carroll, J. B. Psychometric tests as cognitive tasks: A new “structure of intellect. In Resnick, L. B. (Eds.), The nature of intelligence, 1976, New York: Lawrence Erlbaum Associates.Google Scholar
Egan, D. E. Testing based on understanding: Implications from studies of spatial ability. Intelligence, 1979, 3, 1–15.CrossRefGoogle Scholar
Fischer, G. H. The linear logistic test model as an instrument in educational research. Acta Psychologica, 1973, 37, 359–374.CrossRefGoogle Scholar
Kempf, W. F. Dynamic models for the measurement of “traits” in social behavior. In Kempf, W. E., Repp, B. (Eds.), Mathematical models for social psychology, 1977, Bern: Hans Huber Publishers.Google Scholar
Messick, S. Beyond structure: In search of functional models of psychological process. Psychometrika, 1972, 37, 357–375.10.1007/BF02291215CrossRefGoogle Scholar
Pachella, R. G. The interpretation of reaction-time in information-processing research. In Kantowitz, B. H. (Eds.), Human Information-Processing: Tutorials in Performance and Cognition, 1974, Hillsdale, New Jersey: Lawrence Erlbaum Associates.Google Scholar
Pellegrino, J. W., & Glaser, R. Cognitive correlates and components in the analysis of individual differences. Intelligence, 1979.CrossRefGoogle Scholar
Samejima, F. Normal ogive model on the continuous response level in the multi-dimensional latent space. Psychometrika, 1974, 39, 111–121.10.1007/BF02291580CrossRefGoogle Scholar
Scheiblechner, H. Das liernen und losen komplexer denkaufgaben. Z.f. exp.u. angew. Psychol., 1972, 19, 476–505.Google Scholar
Snow, R. E. Theory and research on aptitude processes. Intelligence, 1978, 2, 225–278.10.1016/0160-2896(78)90019-3CrossRefGoogle Scholar
Spada, H. Logistic models of learning and thought. In Spada, H. & Kempf, W. F. (Eds.), Structural models of thinking and learning, 1977, Bern, Switzerland: Hans Huber Publishers.Google Scholar
Sternberg, R. J. Component processes in analogical reasoning. Psychological Review, 1977, 34(4), 356–378.Google Scholar
Sternberg, R. J. The nature of mental abilities. American Psychologist, 1979, 34, 214–230.CrossRefGoogle Scholar
Whitely, S. E. Latent trait models in the study of intelligence. Intelligence, 1980, 4, 97–132.10.1016/0160-2896(80)90010-0CrossRefGoogle Scholar
Whitely, S. E. Modeling aptitude test validity from cognitive components. Journal of Educational Psychology, in press.Google Scholar
Whitely, S. E. Information-processing on intelligence test items. Some response components. Applied Psychological Measurement, 1978, 1, 465–476.CrossRefGoogle Scholar
Whiteley, S. E., & Barnes, G. M. The implications of processing event sequences for theories of analogical reasoning. Memory & Cognition, 1979, 1, 323–331.10.3758/BF03197606CrossRefGoogle Scholar