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Informational Models and Their Uses

Published online by Cambridge University Press:  01 January 2025

Arnold Binder  and
Burton R. Wolin
Arnold Binder
Affiliation:
Indiana University*
Burton R. Wolin
Affiliation:
System Development Corporation
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Abstract

An analysis of the selection and use of informational models in psychological research is undertaken. The axioms of different informational models are presented together with the deductions which have direct empirical application. The models are used to demonstrate many of the inadequacies and inaccuracies involved in the use of information theory in the psychological literature. It is also shown that certain related conceptual ambiguities are understandable in terms of confusions among various models.

Information

Type
Original Paper
Information
Psychometrika , Volume 29 , Issue 1 , March 1964 , pp. 29 - 54
Copyright
Copyright © 1964 Psychometric Society

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Footnotes

*

Most of this article was written while the senior author was summer consultant to the System Development Corporation.

References

Adelson, M., Muckler, F. A., and Williams, A. C. Jr. Verbal learning and message variables related to amount of information. In Quastler, H. (Eds.), Information theory in psychology, Glencoe, Ill.: Free Press, 1955.Google Scholar
Attneave, F. Applications of information theory to psychology, New York: Holt, 1959.Google Scholar
Billingsley, P. Statistical inference for Markov processes, Chicago: Univ. of Chicago Press, 1961.Google Scholar
Billingsley, P. Statistical methods in Markov chains. Ann. math. Statist., 1961, 32, 12–40.CrossRefGoogle Scholar
Bricker, P. D. The identification of redundant stimulus patterns. J. exp. Psychol., 1955, 49, 73–81.CrossRefGoogle ScholarPubMed
Chung, K. L.. Markov chains with stationary transition probabilities, Berlin: Springer-Verlag, 1960.10.1007/978-3-642-49686-8CrossRefGoogle Scholar
Doob, J. L. Stochastic processes, New York: Wiley, 1953.Google Scholar
Estes, W. K. and Suppes, P. Foundations of linear models. In Bush, R. R., Estes, W. K. (Eds.), Studies in mathematical learning theory, Stanford: Stanford Univ. Press, 1959.Google Scholar
Feinstein, A. Foundations of information theory, New York: McGraw-Hill, 1958.CrossRefGoogle Scholar
Feller, W. An introduction to probability theory and its applications. Vol. 1 (2nd ed.), New York: Wiley, 1957.Google Scholar
Garner, W. R. Uncertainty and structure as psychological concepts, New York: Wiley, 1962.Google Scholar
Garner, W. R. and Hake, H. W. The amount of information in absolute judgments. Psychol. Rev., 1951, 58, 446–459.CrossRefGoogle Scholar
Garner, W. R. and McGill, W. J. The relation between information and variance analyses. Psychometrika, 1956, 21, 219–228.CrossRefGoogle Scholar
Hake, H. W. and Garner, W. R. The effect of presenting various numbers of discrete steps on scale reading accuracy. J. exp. Psychol., 1951, 42, 358–366.CrossRefGoogle ScholarPubMed
Hake, H. W. and Hyman, R. Perception of the statistical structure of a random series of binary symbols. J. exp. Psychol., 1953, 45, 64–74.CrossRefGoogle ScholarPubMed
Kemeny, J. G. and Snell, J. L. Finite Markov chains, New York: Van Nostrand, 1960.Google Scholar
Luce, R. D. The theory of selective information and some of its behavioral applications. In Luce, R. D. (Eds.), Developments in mathematical psychology, Glencoe, Ill.: Free Press, 1960.Google Scholar
McGill, W. J. Multivariate information transmission. Psychometrika, 1954, 19, 97–116.CrossRefGoogle Scholar
Miller, G. A. and Frick, F. C. Statistical behavioristics and sequences of responses. Psychol. Rev., 1949, 56, 311–324.CrossRefGoogle ScholarPubMed
Miller, G. A., Heise, G. A., and Lichten, W. The intelligibility of speech as a function of the context of the test materials. J. exp. Psychol., 1951, 41, 329–335.CrossRefGoogle ScholarPubMed
Miller, G. A. and Madow, W. G. On the maximum likelihood estimate of the Shannon-Wiener measure of information. Air Force Cambridge Research Center: Technical Report, 54–75, August 1954.Google Scholar
Morrissette, J. O. and Pearson, W. H. Prediction of behavior under conditions of uncertainty. J. exp. Psychol., 1963, 65, 391–397.10.1037/h0041106CrossRefGoogle Scholar
Newman, E. B. The pattern of vowels and consonants in various languages. Amer. J. Psychol., 1951, 64, 369–379.CrossRefGoogle ScholarPubMed
Newman, E. B. and Gerstman, L. J. A new method for analyzing printed English. J. exp. Psychol., 1952, 44, 114–125.CrossRefGoogle ScholarPubMed
Shannon, C. E. A mathematical theory of communication. Bell syst. tech. J., 1948, 27, 379–423.CrossRefGoogle Scholar
Shannon, C. E. Prediction and entropy of printed English. Bell syst. tech. J., 1951, 30, 50–64.CrossRefGoogle Scholar
Shannon, C. E. and Weaver, W. The mathematical theory of communication, Urbana: Univ. Illinois Press, 1949.Google Scholar
Sharp, H. C. Effect of contextual constraint upon recall of verbal passages. Amer. J. Psychol., 1958, 71, 568–572.CrossRefGoogle ScholarPubMed
Wiener, N. Cybernetics, New York: Wiley, 1948.Google ScholarPubMed