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Some neglected problems in IRT

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Abstract

The paper addresses three neglected questions from IRT. In section 1, the properties of the “measurement” of ability or trait parameters and item difficulty parameters in the Rasch model are discussed. It is shown that the solution to this problem is rather complex and depends both on general assumptions about properties of the item response functions and on assumptions about the available item universe. Section 2 deals with the measurement of individual change or “modifiability” based on a Rasch test. A conditional likelihood approach is presented that yields (a) an ML estimator of modifiability for given item parameters, (b) allows one to test hypotheses about change by means of a Clopper-Pearson confidence interval for the modifiability parameter, or (c) to estimate modifiability jointly with the item parameters. Uniqueness results for all three methods are also presented. In section 3, the Mantel-Haenszel method for detecting DIF is discussed under a novel perspective: What is the most general framework within which the Mantel-Haenszel method correctly detects DIF of a studied item? The answer is that this is a 2PL model where, however, all discrimination parameters are known and the studied item has the same discrimination in both populations. Since these requirements would hardly be satisfied in practical applications, the case of constant discrimination parameters, that is, the Rasch model, is the only realistic framework. A simple Pearsonx 2 test for DIF of one studied item is proposed as an alternative to the Mantel-Haenszel test; moreover, this test is generalized to the case of two items simultaneously studied for DIF.

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References

  • Aczél, J. (1966).Lectures on functional equations and their applications. New York: Academic Press.

    Google Scholar 

  • Alper, T. M. (1987). A classification of all order-preserving homeomorphism groups of the reals that satisfy finite uniqueness.Journal of Mathematical Psychology, 31, 135–154.

    Google Scholar 

  • Andersen, E. B. (1973). A goodness of fit test for the Rasch model.Psychometrika, 38, 123–140.

    Google Scholar 

  • Andersen, E. B. (1985). Estimating latent correlations between repeated testings.Psychometrika, 50, 3–16.

    Google Scholar 

  • Baker, F. B. (1992).Item response theory. New York: Marcel Dekker.

    Google Scholar 

  • Bereiter, C. (1963). Some persisting dilemmas in the measurement of change. In C. W. Harris (Ed.),Problems in measuring change (pp. 3–20). Madison: The University of Wisconsin Press.

    Google Scholar 

  • Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord & M. R. Novick (Eds.),Statistical theories of mental test scores (pp. 395–479). Reading, MA: Addison-Wesley.

    Google Scholar 

  • Churchhouse, R. F. (1981).Handbook of applicable mathmatics, Vol. III. Chichester and New York: J. Wiley.

    Google Scholar 

  • Colonius, H. (1979). Zur Eindeutigkeit der Parameter im Rasch-Modell [On the uniqueness of parameters in the Rasch model].Psychologische Beiträge, 21, 414–416.

    Google Scholar 

  • Cronbach, L. J., & Furby, L. (1970). How should we measure change—or should we?Psychological Bulletin, 74, 68–80.

    Google Scholar 

  • Embretson, S. E. (1991). A multidimensional latent trait model for measuring learning and change.Psychometrika, 56, 495–515.

    Google Scholar 

  • Fischer, G. H. (1972). A measurement model for the effect of mass-media.Acta Psychologica, 36, 207–220.

    Google Scholar 

  • Fischer, G. H. (1974).Einführung in die Theorie psychologischer Tests [Introduction to mental test theory. In German]. Berne: Huber.

    Google Scholar 

  • Fischer, G. H. (1976). Some probabilistic models for measuring change. In D. N. M. de Gruijter & L. J. Th. van der Kamp (Eds.),Advances in psychological and educational measurement (pp. 97–110). New York: J. Wiley.

    Google Scholar 

  • Fischer, G. H. (1981). On the existence and uniqueness of maximum-likelihood estimates in the Rasch model.Psychometrika, 46, 59–77.

    Google Scholar 

  • Fischer, G. H. (1983). Logistic latent trait models with linear constraints.Psychometrika, 48, 3–26.

    Google Scholar 

  • Fischer, G. H. (1987). Applying the principles of specific objectivity and generalizability to the measurement of change.Psychometrika, 52, 565–587.

    Google Scholar 

  • Fischer, G. H. (1988). Spezifische Objektivität: Eine wissenschaftstheoretische Grundlage des Rasch-Modells [Specific objectivity: A theoretical foundation of the Rasch model. In German]. In K. D. Kubinger (Ed.),Moderne Testtheorie (pp. 87–111). Weinhein: Beltz.

    Google Scholar 

  • Fischer, G. H. (1989). An IRT-based model for dichotomous longitudinal data.Psychometrika, 54, 599–624.

    Google Scholar 

  • Fischer, G. H. (1993). Notes on the Mantel-Haenszel procedure and another chi-squared test for the assessment of DIF.Methodika, 7, 88–100.

    Google Scholar 

  • Fischer, G. H. (1995a). Derivations of the Rasch model. In G. H. Fischer & I. W. Molenaar (Eds.),Rasch models. Foundations, recent developments, and applications (pp. 15–38). New York: Springer-Verlag.

    Google Scholar 

  • Fischer, G. H. (1995b). The linear logistic test model. In G. H. Fischer & I. W. Molenaar (Eds.),Rasch models. Foundations, recent developments, and applications (pp. 131–155). New York: Springer-Verlag.

    Google Scholar 

  • Fischer, G. H., & Parzer, P. (1991). An extension of the rating scale model with an application to the measurement of change.Psychometrika, 56, 637–651.

    Google Scholar 

  • Fischer, G. H., & Ponocny, I. (1994). An extension of the partial credit model with an application to the measurement of change.Psychometrika, 59, 177–192.

    Google Scholar 

  • Glas, C. A. W., & Verhelst, N. D. (1995). Testing the Rasch model. In G. H. Fischer & I. W. Molenaar (Eds.),Rasch models. Foundations, recent developments, and applications (pp. 69–95). New York: Springer-Verlag.

    Google Scholar 

  • Guttmann, G., & Etlinger, S. C. (1991). Susceptibility to stress and anxiety in relation to performance, emotion, and personality: The ergopsychometric approach. In C. D. Spielberger, I. G. Sarason, J. Strelau, & J. M. T. Brebner (Eds.),Stress and anxiety, Vol. 13 (pp. 23–52). New York: Hemisphere Publishing.

    Google Scholar 

  • Hambleton, R. K. (1989). Principles and selected applications of item response theory. In R. L. Linn (Ed.),Educational measurement (pp. 147–200). New York: Macmillan, and London: Collier Macmillan.

    Google Scholar 

  • Hamerle, A. (1979). Über die meßtheoretischen Grundlagen von Latent-Trait-Modellen [On measurement-theoretic foundations of latent trait models. In German.]Archiv für Psychologie, 132, 19–39.

    Google Scholar 

  • Hamerle, A. (1982).Latent-Trait-Modelle. [Latent trait models]. Weinheim: Beltz. (In German)

    Google Scholar 

  • Harris, C. W. (Ed.). (1963).Problems in measuring change. Madison: The University of Wisconsin Press.

    Google Scholar 

  • Holland, P. W., & Thayer, D. T. (1988). Differential item functioning and the Mantel-Haenszel procedure. In H. Wainer & H. I. Braun (Eds.),Test validity. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Hulin, C. L., Drasgow, F., & Parsons, C. K. (1983).Item response theory. Application to psychological measurement. Homewood, IL: Dow Jones-Irwin.

    Google Scholar 

  • Irtel, H. (1987). On specific objectivity as a concept in measurement. In E. E. Roskam & R. Suck (Eds.),Progress in mathematical psychology (pp. 35–45). Amsterdam: North-Holland.

    Google Scholar 

  • Irtel, H. (1994). The uniqueness structure of simple latent trait models. In G. H. Fischer & D. Laming (Eds.),Contributions to mathematical psychology, psychometrics, and methodology (pp. 265–275). New York: Springer-Verlag.

    Google Scholar 

  • Johnson, N. L., & Kotz, S. (1969).Distributions in statistics: Discrete distributions, Vol. I. Boston: Houghton Mifflin.

    Google Scholar 

  • Kempf, W. (1977). Dynamic models for the measurement of ‘traits’ in social behavior. In W. Kempf & B. H. Repp (Eds.),Mathematical models for social psychology (pp. 14–58). Berne: Huber.

    Google Scholar 

  • Krantz, D. H., Luce, R. D., Suppes, P., & Tversky, A. (1971).Foundations of measurement, Vol. 1. New York/London: Academic Press.

    Google Scholar 

  • Kubinger, K. D. (1988).Moderne Testtheorie [Modern test theory]. Weinheim: Beltz. (In German)

    Google Scholar 

  • Lord, F. M. (1963). Elementary models for measuring change. In C. W. Harris (Ed.),Problems in measuring change (pp. 21–38). Madison: The University of Wisconsin Press.

    Google Scholar 

  • Lord, F. M. (1980).Applications of items response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Luce, R. D. (1990). Goals, achievements, and limitations of modern fundamental measurement theory. In H. H. Bock (Ed.),Classification and related methods of data analysis (pp. 15–22). Amsterdam: North-Holland.

    Google Scholar 

  • McLane, S., & Birkoff, G. (1988).Algebra (3rd ed.). New York: Chelsea.

    Google Scholar 

  • Narens, L. (1981). On the scales of measurement.Journal of Mathematical Psychology, 24, 249–275.

    Google Scholar 

  • Pfanzagl, J. (1971).Theory of measurement. Würzburg and Vienna: Physica-Verlag.

    Google Scholar 

  • Pfanzagl, J. (1994). On item parameter estimation in certain latent trait models. In G. H. Fischer & D. Laming (Eds.),Contributions to mathematical psychology, psychometrics, and methodology (pp. 249–263). New York: Springer-Verlag.

    Google Scholar 

  • Rasch, G. (1960).Probabilistic models for some intelligence and attainment tests. Copenhagen: Pædagogiske Institut.

    Google Scholar 

  • Rasch, G. (1961). On general laws and the meaning of measurement in psychology.Proceedings of the IV. Berkeley Symposium on mathematical statistics and probability, Vol. IV (pp. 321–333). Berkeley: University of California Press.

    Google Scholar 

  • Rasch, G. (1967). An informal report on a theory of objectivity in comparisons. In L. J. Th. van der Kamp & C. A. J. Vlek (Eds.),Measurement theory (pp. 1–19). Leyden: University of Leyden. (Proceedings of the NUFFIC international summer session in science in “Het Oude Hof”, The Hague, July 14–19, 1996)

    Google Scholar 

  • Rasch, G. (1968, September).A mathematical theory of objectivity and its consequences for model construction. Paper presented at the European Meeting on Statistics, Econometrics, and Management Science, Amsterdam, The Netherlands.

  • Rasch, G. (1972). Objectivitet i samfundsvidenskaberne et metodeproblem [Ojectivity in the social sciences as a methodological problem].National-økonomisk Tidsskrift, 110, 161–196. (In Danish)

    Google Scholar 

  • Rasch, G. (1977). On specific objectivity. An attempt at formalizing the request for generaliy and validity of scientific statements. In M. Blegvad (Ed.),The Danish yearbook of philosophy (pp. 58–94). Copenhagen: Munksgaard.

    Google Scholar 

  • Santner, T. J., & Duffy, D. E. (1989).The statistical analysis of discrete data. New York: Springer-Verlag.

    Google Scholar 

  • Scheiblechner, H. (1995). Isotonic psychometric models (ISOP).Psychometrika, 60, 281–304.

    Google Scholar 

  • Stene, J. (1968). Einführung in Raschs Theorie psychologischer Messung [Introduction to Rasch's theory of psychological measurement]. In G. H. Fischer (Ed.),Psychologische Testtheorie (pp. 229–268). Berne: Huber. (In German)

    Google Scholar 

  • Steyer, R. & Eid, M. (1993).Messen und Testen [Measurement and testing]. Berlin: Springer-Verlag. (In German)

    Google Scholar 

  • Tutz, G. (1989).Latent Trait-Modelle für ordinale Beobachtungen [Latent trait models for ordinal data]. Berlin: Springer-Verlag. (In German)

    Google Scholar 

  • Verhelst, N. D., & Glas, C. A. W. (1993). A dynamic generalization of the Rasch model.Psychometrika, 58, 395–415.

    Google Scholar 

  • Verhelst, N. D., & Glas, C. A. W. (1995). Dynamic generalizations of the Rasch model. In G. H. Fischer & I. W. Molenaar (Eds.),Rasch models. Foundations, recent developments, and applications (pp. 181–201). New York: Springer-Verlag.

    Google Scholar 

  • Wainer, H., & Mislevy, R. (1990). Item response theory, item calibration and proficiency estimation. In H. Wainer (Ed.),Computerized adaptive testing: A primer. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Webster, H., & Bereiter, C. (1963). The reliability of changes measured by mental test scores. In Harris, C. W. (Ed.),Problems in measuring change (pp. 39–59). Madison: The University of Wisconsin Press.

    Google Scholar 

  • Wright, B. D., & Stone, M. H. (1972).Best test design. Chicago: Mesa Press.

    Google Scholar 

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Presidential Address delivered at the 30th Annual Meeting of the Psychometric Society, 16–18 June 1995 in Minneapolis.

This research was supported in part by the Fonds zur Förderung der Wissenschaftlichen Forschung under Grant No. P10118-HIS.

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Fischer, G.H. Some neglected problems in IRT. Psychometrika 60, 459–487 (1995). https://doi.org/10.1007/BF02294324

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