When Can Subscores Have Value?

By S. Haberman. 2008

192 citations recorded by the source corpus.

Subfields: Applied Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/20fac37324d08366b843f6c3333667e322ec7c86

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In Applied Mathematics

In Management Science and Operations Research

Citations in the corpus

Scoring and Modeling Psychological Measures in the Presence of Multidimensionality (2013, methodology): “Partly due to legislation that mandates the reporting of both total and subscale scores across a broad range of achievement domains, psychometric research on the merits of reporting subscale score profiles has been an important topic in educational assessment as reviewed in Sinharay, Puhan, and Habe”
Applying Bifactor Statistical Indices in the Evaluation of Psychological Measures (2016, methodology): “Related to this is the critically important, yet often ignored, determination of whether subscale scores provide unique information above and beyond the total score (see also Haberman, 2008; Haberman, Sinharay, & Puhan, 2008, for related work in education).”
COMPARISON OF MULTIDIMENSIONAL ITEM RESPONSE MODELS: MULTIVARIATE NORMAL ABILITY DISTRIBUTIONS VERSUS MULTIVARIATE POLYTOMOUS ABILITY DISTRIBUTIONS (2008, methodology): “Nonetheless, some restrictions on the size of G are required to ensure that the model parameters are well-enough identified to permit a reasonable rate of convergence (Haberman, 2005a).”
Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art (2008, background): “Just like with other multidimensional models, larger numbers of skills are more challenging to separate empirically than smaller number of skills (Haberman, 2008; Sinhary, Haberman, & Puhan, 2007; Yao & Boughton, 2007; Rupp, 2008a).”
Developing an Instrument for Teacher Feedback : Using the Rasch Model to Explore Teachers' Development of Effective Teaching Strategies and Behaviors (2018, methodology): “Some propose to use exact tests, which can reject the null-hypothesis of one-dimensionality, such as the x2-statistic in confirmatory factor analysis (CFA) (Kline, 2011) or Kelley’s regression formula (Haberman, 2008).”