Abstract
Despite the efforts made in measurement research to deal with the limitations encountered when analyzing unbalanced data via G theory, the research in this area suffers from major restrictions. In this chapter, I introduce the applications of G theory in norm-referenced and criterion—referenced testing. Next, I review the advantages and disadvantages of a variety of methods for handling large and unbalanced data sets. Last, I summarize studies that provide a foundation for the proposed subdividing method.
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© 2001 Springer Science+Business Media New York
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Chiu, C.WT. (2001). Literature in Variance Component Estimations, Large-Scale Assessments, and Missing Data. In: Scoring Performance Assessments Based on Judgements. Evaluation in Education and Human Services, vol 50. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0650-7_2
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DOI: https://doi.org/10.1007/978-94-010-0650-7_2
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-3871-3
Online ISBN: 978-94-010-0650-7
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