Statistical Methods in Speech, Language, and Cognition Research
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This journal self-study course is composed
of papers from a 2019 Research Forum, Advancing Statistical Methods in Speech,
Language, and Hearing Sciences. These selected articles provide advanced-level discussion
about clinically relevant statistical methodologies to give speech-language
pathologists a stronger foundation from which to analyze and understand the
statistical research they come across to decide when and how to apply it in
practice.
Learning Outcomes
You will be able to:
- Describe best practices in basic and more advanced inferential
statistics that avoid errors and find true clinical significance
- Summarize the difference between frequential and Bayesian
analyses as well as potential applications of each
- Describe how and why mixed-effects models are used when
analyzing longitudinal data
- Explain types of clinical questions that could benefit from
machine learning approaches
Articles in This
Course
- Essential Statistical Concepts for Research in Speech, Language, and Hearing
Sciences, by Jacob J. Oleson, Grant D. Brown, & Ryan McCreery, published in Journal
of Speech, Language, and Hearing Research
- The Evolution of Statistical Methods in Speech, Language, and Hearing Sciences,
by Jacob J. Oleson, Grant D. Brown, & Ryan McCreery, published in Journal of Speech,
Language, and Hearing Research
- How Mixed-Effects Modeling Can Advance Our Understanding of Learning and
Memory and Improve Clinical and Educational Practice, by Katherine R. Gordon,
published in Journal of Speech, Language, and Hearing Research
- Functional Logistic Mixed-Effects Models for Learning Curves From Longitudinal
Binary Data, by Giorgio Paulon, Rachel Reetzke, Bharath Chandrasekaran, & Abhra
Sarkar, published in Journal of Speech, Language, and Hearing Research
- The Heterogeneity of Word Learning Biases in Late-Talking Children, by Lynn K.
Perry & Sarah C. Kucker, published in Journal of Speech, Language, and Hearing
Research
- Machine Learning Approaches to Analyze Speech-Evoked Neurophysiological
Responses, by Zilong Xie, Rachel Reetzke and Bharath Chandrasekaran, published in
Journal of Speech, Language, and Hearing Research
Author Information View author disclosures.
Assessment Type
Self-assessment—Think about what you learned and report on the Completion Form how you will use your new knowledge.
To earn continuing education credit, you must complete the learning assessment by the end date below.
Program History and CE Information
Content origination date: October 8, 2020
End date: October 8, 2025
This course is offered for 0.9 ASHA CEUs (Advanced level, Related area).
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