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A Critical Examination of The Analysis of Dichotomous Data

Published online by Cambridge University Press:  01 April 2022

William H. Batchelder
Affiliation:
University of California, Irvine
Louis Narens
Affiliation:
University of California, Irvine

Abstract

This paper takes a critical look at theory-free, statistical methodologies for processing and interpreting data taken from respondents answering a set of dichotomous (yes-no) questions. The basic issue concerns to what extent theoretical conclusions based on such analyses are invariant under a class of “informationally equivalent” question transformations. First the notion of Boolean equivalence of two question sets is discussed. Then Lazarsfeld's latent structure analysis is considered in detail. It is discovered that the best fitting latent model depends on which one of the many informationally equivalent question sets is used. This fact raises a number of methodological problems and pitfalls with latent structure analysis. Related problems with other methodologies are briefly discussed.

Type
Research Article
Copyright
Copyright © 1977 by the Philosophy of Science Association

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Footnotes

The authors would like to thank Albert Ahumada and Jerry Kaiwi for helpful discussions during the development of this paper.

References

REFERENCES

Chow, C. K.Statistical independence and threshold functions.” IEEE Transactions on Electronic Computers EC-14 (1965): 6668.CrossRefGoogle Scholar
Garner, W. R. Uncertainty and Structure as Psychological Concepts. New York: Wiley, 1962.Google Scholar
Hays, W. L. Statistics for Psychologists. New York: Holt, Rinehart, and Winston, 1963.Google Scholar
Krishman, T.On Linear Combinations of Binary Item Scores.” Psychometrika 38 (1973): 291304.CrossRefGoogle Scholar
Lazarsfeld, P. F. and Henry, N. W. Latent Structure Analyses. Boston: Houghton Mifflin Co., 1968.Google Scholar
Shepard, R.A Taxonomy of some Principal Types of Dataand of Multidimensional Methods for their Analysis.” In Shepard, R. N., Romney, A. K. and Nerlove, S. B. (eds.). Multidimensional Scaling, Vol. I, New York: Seminar Press, 1972. Pages 2147.Google Scholar
Sokal, R. R. and Sneath, P. H. A. Principles of Numerical Taxonomy. San Francisco: W. H. Freeman, 1963.Google Scholar
Stevens, S. S.Measurement and Man.” Science 127 (1958): 383389.CrossRefGoogle ScholarPubMed
Watanabe, S. Knowing and Guessing. New York: John Wiley and Sons, 1969.Google Scholar