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    • 3310 Linguistics and Language (5)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 White noise facilitates new-word learning from context Angwin, Anthony J.; Wilson, Wayne J.; Ripollés, Pablo. - : Academic Press, 2019 BASE Show details 2 The ‘acoustic health’ of primary school classrooms in Brisbane, Australia Wilson, Wayne J.; Downing, Cerys; Perrykkad, Kelsey. - : Taylor & Francis, 2019 BASE Show details 3 Reading development in children with cochlear implants who communicate via spoken language: A psycholinguistic investigation Angwin, Anthony J.; Arnott, Wendy L.; Wilson, Wayne J.. - : American Speech - Language - Hearing Association, 2019 BASE Show details 4 The impact of auditory white noise on semantic priming Angwin, Anthony J.; Wilson, Wayne J.; Copland, David A.. - : Academic Press, 2018 BASE Show details 5 Predicting language difficulties in middle childhood from early developmental milestones: a comparison of traditional regression and machine learning techniques Armstrong, Rebecca; Symons, Martyn; Scott, James G.; Arnott, Wendy L.; Copland, David A.; McMahon, Katie L.; Whitehouse, Andrew J. O.. - : American Speech - Language - Hearing Association, 2018 Abstract: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) broader developmental skills (motor, social, and adaptive) at 3 years old on language outcomes at 10 years old.Participants (N = 1,322) were drawn from the Western Australian Pregnancy Cohort (Raine) Study (Straker et al., 2017). A general developmental screener, the Infant Monitoring Questionnaire (Squires, Bricker, & Potter, 1990), was completed by caregivers at the 3-year follow-up. Language ability at 10 years old was assessed using the Clinical Evaluation of Language Fundamentals-Third Edition (Semel, Wiig, & Secord, 1995). Logistic regression models and interpretable machine learning algorithms were used to assess predictive abilities of early developmental milestones for later language outcomes.Overall, the findings showed that prediction accuracies were comparable between logistic regression and machine learning models using communication-only performance as well as performance on communication and broader developmental domains to predict language performance at 10 years old. Decision trees are incorporated to visually present these findings but must be interpreted with caution because of the poor accuracy of the models overall.The current study provides preliminary evidence that machine learning algorithms provide equivalent predictive accuracy to traditional methods. Furthermore, the inclusion of broader developmental skills did not improve predictive capability. Assessment of language at more than 1 time point is necessary to ensure children whose language delays emerge later are identified and supported.https://doi.org/10.23641/asha.6879719. Keyword: 1203 Language and Linguistics; 3310 Linguistics and Language; 3616 Speech and Hearing; Language and Linguistics; Linguistics and Language; Speech and Hearing URL: https://espace.library.uq.edu.au/view/UQ:08242ab BASE Hide details

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