Abstract

The purpose of this study was to explore the relationship of three subskills associated with word decoding. The skills utilized for this study were phonological, rapid automatized naming (RAN), and orthographic processing. To do this, six separate models were utilized to define different ways that these three subskills (represented as factors) related to one another, with the goal of finding which model provided the best prediction of word decoding. A sample of 100 subjects from the PAIRW normative sample was used for this study. Results of structural equation modeling, utilizing the AMOS 4.0 program, revealed that using all three subskills concurrently provided the best-fitting model. Contrary to previous research, orthographic, rather than phonological, processing skills were found to be the best predictor of word decoding. RAN was found to be the second best predictor, but only indirectly through the Phonological and Orthographic factors. Moreover, when RAN was utilized as a predictor of orthographic and phonological processing, it provided a better-fitting model than when orthographic and phonological processing were used as predictors of RAN. Utilizing RAN as a predictor of both phonological and orthographic processing was found to provide a better-fitting model than when RAN was used to predict either the Phonological or Orthographic factor alone. The relevance of utilizing all three subskills in psychoeducational assessment is discussed, as well as implications for future research.

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