Modeling item-level spelling variance in adults : Providing further insights into lexical quality

Purpose The lexical quality (LQ) hypothesis predicts that a skilled reader’s lexicon will be inhabited by a range of low- to high-quality items, and the probability of representing a word with high quality varies as a function of person-level, word-level, and item-specific variables. These predictions were tested with spelling accuracy as a gauge of LQ. Method Item-response based crossed random effects models explored simultaneous contributions of person-level (e.g. participant’s decoding skill), word-level (e.g. word’s transparency rating), item-specific (e.g. participant’s familiarity with specific word), and person-by-word interaction predictors (e.g. decoding by transparency rating interaction) to the spelling of 25 commonly misspelled irregular English words in 61 undergraduate university students (M = 19.4 years, 70.49% female, 39.34% Hispanic, 81.97% White). Results Substantial variance among individuals in item-level spelling accuracy was accounted for by person-level decoding skill; item-specific familiarity, proportion of schwas correctly represented, and correctly identifying the word from its mispronunciation; and an interaction of transparency rating by general decoding skill. Conclusions Consistent with the LQ hypothesis, results suggest that one’s ability to form a high-quality lexical representation of a given word depends on a complex combination of person-level abilities, word-level characteristics, item-specific experiences, and an interaction between person- and word-level influences

Early prediction of reading risk in fourth grade : A combined latent class analysis and classification tree approach

Purpose Fourth grade typically involves shifting the instruction from learning to read to reading to learn, which can cause students to struggle. However, early reading intervention guided by assessment has demonstrated effectiveness in preventing later reading difficulties (RD). This study presents a classification and regression tree (CART) model predicting fourth-grade reading groups using first-grade measures. Method Students were assessed in first and fourth grade (N = 452). Fourth-grade groups were determined using latent class analysis based on word reading and reading comprehension measures with a cut-point at the 15th percentile. A CART model was trained to determine the best decision rules to classify students at risk of developing later RD and compared to a logistic regression model. Results Important first-grade predictors included a mix of oral language and foundational word-reading skills with final classification accuracy estimates of .90 AUC, .91 sensitivity, and .75 specificity. Conclusion While the CART and logistic regression models’ classification accuracy was similar, CART has the advantage of offering a more intuitive way for practitioners to determine risk. Multivariate screening can be time-consuming, but CART models offer the potential to reduce false positives and guide targeted interventions, leading to better use of school resources

Modeling complex word reading : Examining influences at the level of the word and child on mono-and polymorphemic word reading

Purpose The probability of a child reading a word correctly is influenced by both child skills and properties of the word. The purpose of this study was to investigate child-level skills (set for variability and vocabulary), word-level properties (concreteness), word structure (mono- vs polymorphemic), and interactions between these properties and word structure within a comprehensive item-level model of complex word reading. This study is unique in that it purposely sampled both mono- and polymorphemic polysyllabic words. Method A sample of African American (n = 69) and Hispanic (n = 6) students in grades 2–5 (n = 75) read a set of mono- and polymorphemic polysyllabic words (J = 54). Item-level responses were modeled using cross-classified generalized random-effects models allowing variance to be partitioned between child and word while controlling for other important child factors and word features. Results Set for variability and the interaction between concreteness and word structure (i.e., mono- vs polymorphemic) were significant predictors. Higher probabilities of reading poly- over monomorphemic words were identified at lower levels of concreteness with the opposite at higher levels of concreteness. Conclusions Results indicate important predictors at both the child- and word-level and support the importance of morphological structure for reading abstract polysyllabic words

Set for variability as a critical predictor of word reading : Potential implications for early identification and treatment of dyslexia

Quasiregular orthographies such as English contain substantial ambiguities between orthography and phonology that force developing readers to acquire flexibility during decoding of unfamiliar words, a skill referred to as a “set for variability” (SfV). The ease with which a child can disambiguate the mismatch between the decoded form of a word and its actual lexical phonological form has been operationalized using the SfV mispronunciation task (e.g., the word wasp is pronounced to rhyme with clasp [i.e., /wæsp/] and the child must recognize the actual pronunciation of the word to be /wɒsp/). SfV has been shown to be a significant predictor of word reading variance. However, little is known about the relative strength of SfV as a predictor of word reading compared to other well-established predictors or the strength of this relationship in children with dyslexia. To address these questions, we administered the SfV task to a sample of grade 2–5 children (N = 489) along with other reading related measures. SfV accounted for 15% unique variance in word reading above and beyond other predictors, whereas phonological awareness (PA) accounted for only 1%. Dominance analysis indicated SfV is the most powerful predictor, demonstrating complete statistical dominance over other variables including PA. Quantile regression revealed SfV is a stronger predictor at lower levels of reading skill, indicating it may be an important predictor in students with dyslexia. Results suggest that SfV is a powerful and potentially highly sensitive predictor of early reading difficulties and, therefore, may be important for early identification and treatment of dyslexia