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Purpose Research in communication sciences and disorders frequently involves the collection of clusters of observations, such as a series of scores for each individual receiving treatment over the course of an intervention study. However, little discipline-specific guidance is currently available on the subject of building and interpreting multilevel models. This article offers a tutorial on multilevel models, using notation from the R statistical software, and discusses their implications for research in communication sciences and disorders. Method This tutorial introduces multilevel models and contrasts them with other methods to analyze repeated measures data, such as repeated measures analysis of variance or standard linear regression. It also provides guidance on interpreting the components of a multilevel model and selecting the best-fitting model. Finally, these models are illustrated through an analysis of real data from a study of speech production training in second-language speakers of English. Conclusions As a flexible method that can increase the rigor of modeling for clustered data, multilevel modeling represents an important tool for research in communication disorders. Given their increasingly prominent role in the analysis of experimental data in communication sciences, it is important for researchers to be familiar with the basics of building and interpreting these models.
This article was published in the following journal.
Name: Journal of speech, language, and hearing research : JSLHR
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The statistical manipulation of hierarchically and non-hierarchically nested data. It includes clustered data, such as a sample of subjects within a group of schools. Prevalent in the social, behavioral sciences, and biomedical sciences, both linear and nonlinear regression models are applied.
Communication, in the sense of cross-fertilization of ideas, involving two or more academic disciplines (such as the disciplines that comprise the cross-disciplinary field of bioethics, including the health and biological sciences, the humanities, and the social sciences and law). Also includes problems in communication stemming from differences in patterns of language usage in different academic or medical disciplines.
Disorders of verbal and nonverbal communication caused by receptive or expressive LANGUAGE DISORDERS, cognitive dysfunction (e.g., MENTAL RETARDATION), psychiatric conditions, and HEARING DISORDERS.
Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment.
Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression.