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Additional Evidence Based on the Internal Structure of the Instrument

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Instrument Development in the Affective Domain

Abstract

In many ways, Chap. 5 is an extension of the methods and techniques used to gather evidence based on the internal structure of the instrument and continues to describe the latent variable approach to instrument development. In this chapter, we introduce two common instrument development situations where discrete mathematical structures are encountered: latent class analysis (LCA) and item response theory (IRT). In LCA, both the latent variable and the indicator variable are best represented by a categorical structure. In IRT, the latent trait is continuous, but the items are the items are categorical. IRT has historically been used in educational achievement applications, however, it is gaining popularity in some affective characteristic measurement scenarios. The last section of the chapter is devoted to the topic of measurement invariance and the analytic techniques that allow instrument developers to explore whether the scale functions in the same manner (exhibits the same internal structure) across subgroups. If the items that reflect their latent constructs and the connections between the constructs operate in a fundamentally different way depending on group membership, cross group comparisons become difficult, if not impossible. This chapter discusses the most common statistical techniques (along with examples) for establishing invariance for both scenarios where the indicators are either continuous or categorical.

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Notes

  1. 1.

    Material from Gable et al. (2011) included with permission from Sage Publications.

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Correspondence to D. Betsy McCoach .

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McCoach, D.B., Gable, R.K., Madura, J.P. (2013). Additional Evidence Based on the Internal Structure of the Instrument. In: Instrument Development in the Affective Domain. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7135-6_5

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