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Bayesian Generalized Linear Mixed-Model Analysis of Language Samples: Detecting Patterns in Expository and Narrative
Gavin Collins1, Jennifer P Lundine2,3, Eloise Kaizar1
1Department of Statistics, The Ohio State University, Columbus.
Journal of Speech, Language, and Hearing Research : JSLHR
|March 30, 2021
Summary
Generalized linear mixed-models (GLMM) and Bayesian methods revealed significant differences in language productivity and lexical diversity in adolescents with traumatic brain injury (TBI). These advanced statistical approaches offer greater confidence in analyzing complex communication science data.
Area of Science:
- Communication Sciences
- Neuroscience
- Developmental Psychology
Background:
- Generalized linear mixed-models (GLMM) and Bayesian methods offer robust frameworks for analyzing complex data in communication sciences.
- Language sample analysis is crucial for understanding discourse patterns, especially in clinical populations.
Purpose of the Study:
- To demonstrate the utility of Bayesian GLMM in analyzing discourse patterns in adolescents.
- To compare the language sample characteristics of adolescents with traumatic brain injury (TBI) to typically developing peers.
Main Methods:
- Collected language samples from 55 adolescents (ages 13-18), including 5 with TBI.
- Developed Bayesian GLMMs to analyze parameters of productivity, syntactic complexity, and lexical diversity.
- Examined the influence of age, sex, TBI history, socioeconomic status, and discourse type.
Main Results:
- Substantial differences in productivity and lexical diversity were found between adolescents with and without TBI.
- Syntactic complexity differences were more moderate.
- Older adolescents and those with higher socioeconomic status generally exhibited more advanced discourse.
Conclusions:
- Bayesian GLMMs provide more informative and reliable results than traditional statistical methods for language sample analysis.
- These advanced methods are recommended for wider adoption in communication sciences research.
- Significant discourse differences highlight the impact of TBI on language development.
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