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A Base-Free Measure of Change

Published online by Cambridge University Press:  01 January 2025

Ledyard R Tucker ,
Fred Damarin  and
Samuel Messick
Ledyard R Tucker
Affiliation:
University of Illinois
Fred Damarin
Affiliation:
Educational Testing Service
Samuel Messick
Affiliation:
Educational Testing Service
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Abstract

A model for the measurement of the discrepancy between two scores is presented and discussed as a paradigm for the study of growth or experimentally produced change. The model assumes two tests or measures differing in complexity, and it analyzes the true difference between the test scores into a component that is entirely dependent on the first or base-line test and a second component that is entirely independent of it. Equations for estimating both components are given and these are compared with other measurement efforts with similar goals.

Type
Original Paper
Information
Psychometrika , Volume 31 , Issue 4 , December 1966 , pp. 457 - 473
Copyright
Copyright © 1966 Psychometric Society

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Footnotes

*

This research was supported in part by a grant from the United States Public Health Service, National Institute of Mental Health No. M-4186. We are greatly indebted to Harold Gulliksen and Frederic Lord for a careful reading of this manuscript and for their many valuable suggestions. The work of Gerri Nagy and Marie Davis in typing and proof-reading is gratefully acknowledged.

References

Berkson, J. Are there two regressions?. J. Amer. statist. Ass., 1950, 45, 164–180.CrossRefGoogle Scholar
DuBois, P. H. Multivariate correlational analysis, New York: Harper, 1957.Google Scholar
Gulliksen, H. Theory of mental tests, New York: Wiley, 1950.CrossRefGoogle Scholar
Harris, C. W. Some problems in the description of change. Educ. psychol. Measmt, 1962, 22, 303–319.CrossRefGoogle Scholar
Harris, C. W. Problems in measuring change, Madison: Univ. Wisconsin Press, 1963.Google Scholar
Lacey, J. I. The evaluation of autonomic responses: Toward a general solution. Ann. New York Acad. Sci., 1956, 67, 123–164.CrossRefGoogle Scholar
Lacey, J. I. and Lacey, B. C. The law of initial value in the longitudinal study of autonomic constitution: Reproducibility of autonomic responses and response patterns over a four year interval. Ann. New York Acad. Sci., 1962, 98, 1257–1290.CrossRefGoogle Scholar
Lord, F. M. The measurement of growth. Educ. psychol. Measmt, 1956, 16, 421–437.CrossRefGoogle Scholar
Lord, F. M. Further problems in the measurement of growth. Educ. psychol. Measmt, 1958, 18, 437–451.CrossRefGoogle Scholar
Lord, F. M. Large-sample covariance analysis when the control variable is fallible. J. Amer. statist. Ass., 1960, 55, 307–321.CrossRefGoogle Scholar
Lord, F. M. Measurement of academic growth—statistical problems, Princeton, N. J.: Educ. Test. Serv., 1962.Google Scholar
Lord, F. M. Elementary models for measuring change. In Harris, C. W. (Eds.), Problems in measuring change, Madison: Univ. Wisconsin Press, 1963.Google Scholar
Madansky, A. The fitting of straight lines when both variables are subject to error. J. Amer. statist. Ass., 1959, 54, 173–205.CrossRefGoogle Scholar
Manning, W. H. and DuBois, P. H. Correlational methods in research on human learning. Percept. mot. Skills, 1962, 15, 287–321.CrossRefGoogle Scholar
McNemar, Q. On growth measurement. Educ. psychol. Measmt, 1958, 18, 47–55.CrossRefGoogle Scholar
Messick, S. and Hills, J. K. Objective measurement of personality: cautiousness and intolerance of ambiguity. Educ. psychol. Measmt, 1960, 20, 685–698.CrossRefGoogle Scholar
Stouffer, S. A. Evaluating the effect of inadequately measured variables in partial correlation analysis. J. Amer. statist. Ass., 1936, 31, 348–360.CrossRefGoogle Scholar
Stouffer, S. A. Reliability coefficients in a correlation matrix. Psychometrika, 1936, 1, 17–20.CrossRefGoogle Scholar
Thomson, G. H. A formula to correct for the effect of errors of measurement on the correlation of initial values with gains. J. exp. Psychol., 1924, 7, 321–324.CrossRefGoogle Scholar
Thomson, G. H. An alternative formula for the true correlation of initial values with gains. J. exp. Psychol., 1925, 8, 323–324.CrossRefGoogle Scholar
Zieve, L. Note on the correlation of initial scores with gains. J. educ. Psychol., 1940, 31, 391–394.CrossRefGoogle Scholar