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Related Experiment Video

Updated: Jan 26, 2026

Assessment and Communication for People with Disorders of Consciousness

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Multilevel Models for Communication Sciences and Disorders.

Daphna Harel¹, Tara McAllister¹

¹NYU Steinhardt School of Culture, Education, and Human Development, New York, NY.

Journal of Speech, Language, and Hearing Research : JSLHR

|April 11, 2019

Summary

Multilevel modeling offers a flexible approach for analyzing clustered data in communication sciences and disorders research. This tutorial guides researchers in building and interpreting these powerful statistical models for intervention studies.

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Area of Science:

Communication Sciences and Disorders
Statistics
Psychology

Background:

Research in communication sciences and disorders often yields clustered data, such as repeated measures from individuals over time.
Existing methods like repeated measures ANOVA may not adequately handle complex data structures.
There is a need for discipline-specific guidance on multilevel modeling.

Purpose of the Study:

To provide a tutorial on building and interpreting multilevel models for communication sciences and disorders research.
To illustrate the application of multilevel models using R statistical software.
To enhance the rigor of analyzing clustered and repeated measures data.

Main Methods:

Introduction to multilevel models, contrasting them with traditional methods (e.g., repeated measures ANOVA, linear regression).
Guidance on interpreting model components and selecting the best-fitting model.
Demonstration using real data from a speech production training study.

Main Results:

Multilevel modeling provides a flexible and rigorous framework for analyzing clustered data.
The tutorial demonstrates practical application and interpretation of these models.
Effective use of multilevel models can improve the analysis of experimental data in communication disorders.

Conclusions:

Multilevel modeling is an essential tool for researchers in communication disorders due to its flexibility with clustered data.
Familiarity with building and interpreting multilevel models is increasingly important for analyzing experimental data.
This approach enhances the statistical rigor of research in the field.