Data-driven subclassification of speech sound disorders in preschool children

DOI

10.1044/2014_JSLHR-S-12-0193

Authors

Jennell C. Vick, Case Western Reserve University
Thomas F. Campbell, The University of Texas at Dallas
Lawrence D. Shriberg, Waisman Center
Jordan R. Green, MGH Institute of Health Professions
Klaus Truemper, The University of Texas at Dallas
Heather Leavy Rusiewicz, Duquesne University
Christopher A. Moore, Department of Veterans Affairs

Document Type

Journal Article

Publication Date

12-1-2014

Publication Title

Journal of Speech, Language, and Hearing Research

Volume

57

Issue

6

First Page

2033

Last Page

2050

ISSN

10924388

Abstract

Purpose: The purpose of the study was to determine whether distinct subgroups of preschool children with speech sound disorders (SSD) could be identified using a subgroup discovery algorithm (SUBgroup discovery via Alternate Random Processes, or SUBARP). Of specific interest was finding evidence of a subgroup of SSD exhibiting performance consistent with atypical speech motor control.

Open Access

Green Accepted

Preprint

Link to Author Manuscript

Repository Citation

Vick, J., Campbell, T., Shriberg, L., Green, J., Truemper, K., Rusiewicz, H., & Moore, C. (2014). Data-driven subclassification of speech sound disorders in preschool children. Journal of Speech, Language, and Hearing Research, 57 (6), 2033-2050. https://doi.org/10.1044/2014_JSLHR-S-12-0193