Augmented Scores-"Borrowing Strength" to Compute Scores Based on Small Numbers ofltems

By Howard Wainer, Jack L. Vevea, Fabian Camacho, B. Reeve, Kathleen Rees Rosa, Lauren Nelson, Kimberly Swygert, D. Thissen. 2001

86 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6269b9af02164658cdceb7794fab921c9fbe14b6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

When Can Subscores Have Value? (2008, methodology): “To overcome limited reliability of subscores, one may use regression to produce a linear combination of subscores that provides a more accurate estimate of the proficiency measured by the subscore than is provided by the intuitive subscore measure (Wainer et al., 2001; Yen, 1987).”
Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring (2005, methodology): “The simultaneous estimation procedure discussed in this article is akin to the method employed by Wainer et al. (2001) in that both augment scores on one test by using information from other tests, and, as our analyses show, under a variety of testing conditions the two approaches yield very…”
Simultaneous Estimation of Overall and Domain Abilities: A Higher-Order IRT Model Approach (2009, methodology): “In the former, depending on the disparity of the domains, the general or overall ability estimate may not be valid because of the extent to which the unidimensional assumption is violated; whereas in the latter, with the correlation between the domain abilities ignored, the multiple applications of ”
A Multidimensional Item Response Modeling Approach for Improving Subscale Proficiency Estimation and Classification (2007, methodology): “Wainer et al. (2001) proposed an augmentation to Yen’s method, by allowing the information from the other subscale scores (they note that Yen only used the total test score) to help stabilize each diagnostic subscale score, with each item loading on only one subscale.”
A Cognitive Diagnosis Model for Cognitively Based Multiple-Choice Options (2009, background): “However, aside from unreliability (e.g., de la Torre & Patz, 2005; Wainer et al., 2001), the information provided by cluster scores is superficial and may not reflect deeper underlying processes involved in learning and problem solving.”