Abstract
There are two approaches that can be taken with regards to a data–model relationship. The first and most common approach is that of item response theory (IRT), where the model describes the data. If the data do not fit the model, another model with more parameters is chosen. The second and less common approach is that of Rasch measurement theory, where the model is an operationalization of fundamental requirements of measurement. If the data do not fit the model, reasons for the misfit are investigated as anomalies.
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References
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Further Reading
Andrich, D. (1989). Distinction between assumptions and requirements in the social sciences. In J. A. Keats, R. Taft, & S. H. Lovibond (Eds.), Proceedings of the XXIVth International Congress of Psychology, Mathematical and Theoretical Systems (Vol. 4, pp. 7–16). B.V. North Holland: Elsevier Science Publications.
Andrich, D. (2018). Advances in social measurement: A Rasch measurement theory. In F. Guillemin, A. Leplège, S. Briançon, E. Spitz, & J. Coste (Eds.), Perceived health and adaptation in chronic disease: Stakes and future challenge (Chapter 7, pp. 66–91). Taylor and Francis: CRCS Press.
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Thurstone, L. L. (1954). The measurement of values. Psychological Review,61(1), 47–58.
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Exercises
Exercises
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1.
Summarize, in no more than 200 words, the idea of a paradigm in research and in scientific research.
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2.
Summarize, in no more than 300 words, the distinction between the two approaches to measurement outlined in this chapter. Relate this distinction to the idea of paradigms of research and to how models are used in these two paradigms.
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Andrich, D., Marais, I. (2019). Comparisons and Contrasts Between Item Response Theory and Rasch Measurement Theory. In: A Course in Rasch Measurement Theory. Springer Texts in Education. Springer, Singapore. https://doi.org/10.1007/978-981-13-7496-8_19
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