Predicting word reading ability : a quantile regression study

McIlraith, Autumn (2018) Predicting word reading ability : a quantile regression study. Journal of Research in Reading, 41 (1). pp. 79-96. ISSN 0141-0423

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Abstract

Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and kindergarten measures of letter knowledge, phonological awareness, rapid automatised naming, sentence repetition, vocabulary and mother’s education to predict first-grade word reading. Predictors generally varied in significance across levels of word reading. Notably, rapid automatised naming was a significant unique predictor for average and good readers but not poor readers. Letter knowledge was generally a stronger unique predictor for poor and average readers than good readers. Well-known word reading predictors varied in significance at different points along the word read- ing distribution. Results have implications for early identification and statistical analyses of reading-related outcomes.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Research in Reading
Additional Information:
This is the peer reviewed version of the following article:McIlraith, A. L., and Language and Reading Research Consortium (2018) Predicting word reading ability: a quantile regression study. Journal of Research in Reading, 41: 79–96. doi: 10.1111/1467-9817.12089 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/1467-9817.12089/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3300/3304
Subjects:
?? educationpsychology (miscellaneous)developmental and educational psychology ??
ID Code:
82778
Deposited By:
Deposited On:
11 Nov 2016 13:36
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Oct 2024 23:43