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1
Effects of Phonomotor Therapy and Semantic Feature Analysis on Discourse Production
In: Speech and Hearing Sciences Faculty Publications and Presentations (2021)
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2
Assessment of Communication Disorders: New Frontiers and Challenges.
In: Speech and Hearing Sciences Faculty Publications and Presentations (2021)
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3
Computer Adaptive Testing for the Assessment of Anomia Severity
In: Speech and Hearing Sciences Faculty Publications and Presentations (2021)
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4
Algorithmic Classification of Paraphasias (Fergadiotis et al., 2016) ...
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5
Algorithmic Classification of Paraphasias (Fergadiotis et al., 2016) ...
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6
Code-Switching and Language Proficiency in Bilingual Children with and Without Developmental Language Disorder.
In: Speech and Hearing Sciences Faculty Publications and Presentations (2021)
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7
Code-Switching and Language Proficiency in Bilingual Children With and Without Developmental Language Disorder
In: J Speech Lang Hear Res (2021)
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8
Psychometric Evaluation of Lexical Diversity Indices in Spanish Narrative Samples From Children With and Without Developmental Language Disorder
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
Abstract: Purpose The purpose of the current study was to examine construct validity evidence for the following 4 lexical diversity measures for use in Spanish narrative samples of children with developmental language disorder and typical language development (TLD): (a) type–token ratio (TTR; Chotlos, 1944; Templin, 1957), (b) hypergeometric distribution D (McCarthy & Jarvis, 2010), (c) measure of textual lexical diversity (MTLD; McCarthy, 2005), and (d) moving-average TTR (MATTR; Covington & McFall, 2010). Method A multiple-group, confirmatory factor analytic stepwise procedure was applied to examine factorial invariance in a sample of 435 monolingual Spanish-speaking children (335 with TLD and 100 with specific language impairment). Results MATTR was the strongest indicator of the lexical diversity of a sample and demonstrated measurement invariance across children with TLD and specific language impairment. MTLD scores included some noise at different levels as a function of the length of a sample, especially for short language samples, but differences in relation to MATTR were relatively small. The validity of hypergeometric distribution D and TTR score interpretations was low, as the scores covaried systematically with length, with TTR being the poorest measure of lexical diversity. Conclusion Results support the use of MATTR and MTLD as measures of lexical diversity and should assist clinicians and researchers in the selection of lexical diversity measures to minimize bias in score interpretations when conducting language sample analyses.
Keyword: Speech and Rhetorical Studies
URL: https://pdxscholar.library.pdx.edu/sphr_fac/38
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9
Empirical Evaluation of Computer-Adaptive Alternate Short Forms for the Assessment of Anomia Severity.
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
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10
Predicting Confrontation Naming Item Difficulty
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
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11
Enhancing the Efficiency of Confrontation Naming Assessment for Aphasia Using Computer Adaptive Testing
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
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12
Effects of Phonomotor Treatment on Discourse Production
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
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13
Modeling Confrontation Naming and Discourse Informativeness Using Structural Equation Modeling
In: Speech and Hearing Sciences Faculty Publications and Presentations (2019)
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14
Computer-adaptive assessment of anomia (Hula et al., 2019) ...
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15
Enhancing anomia assessment (Fergadiotis et al., 2019) ...
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16
Computer-adaptive assessment of anomia (Hula et al., 2019) ...
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17
Enhancing anomia assessment (Fergadiotis et al., 2019) ...
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18
Empirical Evaluation of Computer-Adaptive Alternate Short Forms for the Assessment of Anomia Severity
In: J Speech Lang Hear Res (2019)
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19
Effects of Phonomotor Treatment on discourse production
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20
Predicting confrontation naming item difficulty
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