Assessing unidimensionality: A comparison of Rasch modeling, Parallel analysis, and TETRAD

Chong Ho Yu, Sharon Osborn Popp, Samuel DiGangi, Angel Jannasch-Pennell

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20 Citations (Scopus)

Abstract

The evaluation of assessment dimensionality is a necessary stage in the gathering of evidence to support the validity of interpretations based on a total score, particularly when assessment development and analysis are conducted within an item response theory (IRT) framework. In this study, we employ polytomous item responses to compare two methods that have received increased attention in recent years (Rasch model and Parallel analysis) with a method for evaluating assessment structure that is less well-known in the educational measurement community (TETRAD). The three methods were all found to be reasonably effective. Parallel Analysis successfully identified the correct number of factors and while the Rasch approach did not show the item misfit that would indicate deviation from clear unidimensionality, the pattern of residuals did seem to indicate the presence of correlated, yet distinct, factors. TETRAD successfully confirmed one dimension in the single-construct data set and was able to confirm two dimensions in the combined data set, yet excluded one item from each cluster, for no obvious reasons. The outcomes of all three approaches substantiate the conviction that the assessment of dimensionality requires a good deal of judgment.

Original languageEnglish (US)
Pages (from-to)1-19
Number of pages19
JournalPractical Assessment, Research and Evaluation
Volume12
Issue number14
StatePublished - 2007

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Assessing unidimensionality : A comparison of Rasch modeling, Parallel analysis, and TETRAD. / Yu, Chong Ho; Popp, Sharon Osborn; DiGangi, Samuel; Jannasch-Pennell, Angel.

In: Practical Assessment, Research and Evaluation, Vol. 12, No. 14, 2007, p. 1-19.

Research output: Contribution to journalArticle

Yu, Chong Ho ; Popp, Sharon Osborn ; DiGangi, Samuel ; Jannasch-Pennell, Angel. / Assessing unidimensionality : A comparison of Rasch modeling, Parallel analysis, and TETRAD. In: Practical Assessment, Research and Evaluation. 2007 ; Vol. 12, No. 14. pp. 1-19.
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