Literature DB >> 17675608

A performance curve for assessing change in Percentage of Consonants Correct Revised (PCC-R).

Thomas F Campbell1, Christine Dollaghan, Janine E Janosky, P David Adelson.   

Abstract

PURPOSE: Interpreting the rapidly changing speech skills of young children recovering from neurological injury is difficult because developmental expectations are generally available only at relatively lengthy intervals (e.g., 6 or 12 months). In this research note, the authors describe the process of generating a Percentage of Consonants Correct-Revised (PCC-R; L. D. Shriberg, D. Austin, B. A. Lewis, J. L. McSweeny, & D. L. Wilson, 1997a) performance curve and illustrate some of its applications for assessing change in performance over time.
METHOD: The authors compiled mean PCC-R scores from 16 samples of typically developing children (18-172 months) and used curve fitting to test more than 11,000 statistical models of monthly growth in PCC-R. They selected a parsimonious and developmentally plausible model with R(2) = .9839 (p < .0005) and used it to generate the PCC-R, standard deviation, and standard error expected at each monthly age.
RESULTS: The PCC-R performance curve distinguished among 65 children (37-57 months of age) diagnosed independently with normal or disordered speech with a high degree of success. More important, the PCC-R performance curve can be used to identify the points at which children (18-172 months) recovering from neurological injury achieve normal-range consonant production.
CONCLUSION: The curve-fitting approach holds promise as a means of interpreting temporal variations in speech production at a finer grain than existing normative data currently allow.

Entities:  

Mesh:

Year:  2007        PMID: 17675608     DOI: 10.1044/1092-4388(2007/077)

Source DB:  PubMed          Journal:  J Speech Lang Hear Res        ISSN: 1092-4388            Impact factor:   2.297


  7 in total

1.  Recommendations for the use of common outcome measures in pediatric traumatic brain injury research.

Authors:  Stephen R McCauley; Elisabeth A Wilde; Vicki A Anderson; Gary Bedell; Sue R Beers; Thomas F Campbell; Sandra B Chapman; Linda Ewing-Cobbs; Joan P Gerring; Gerard A Gioia; Harvey S Levin; Linda J Michaud; Mary R Prasad; Bonnie R Swaine; Lyn S Turkstra; Shari L Wade; Keith O Yeates
Journal:  J Neurotrauma       Date:  2011-08-24       Impact factor: 5.269

2.  Factors Influencing Elementary and High-School Aged Cochlear Implant Users.

Authors:  Emily A Tobey; Ann E Geers; Madhu Sundarrajan; Janet Lane
Journal:  Ear Hear       Date:  2011-02-01       Impact factor: 3.570

3.  Identifying residual speech sound disorders in bilingual children: a Japanese-english case study.

Authors:  Jonathan L Preston; Ayumi Seki
Journal:  Am J Speech Lang Pathol       Date:  2011-03-08       Impact factor: 2.408

4.  Spoken word recognition in adolescent cochlear implant users during quiet and multispeaker babble conditions.

Authors:  Emily A Tobey; Sujin Shin; Madhu Sundarrajan; Ann E Geers
Journal:  Otol Neurotol       Date:  2011-04       Impact factor: 2.311

5.  Phonological awareness and types of sound errors in preschoolers with speech sound disorders.

Authors:  Jonathan Preston; Mary Louise Edwards
Journal:  J Speech Lang Hear Res       Date:  2009-08-28       Impact factor: 2.297

6.  Data-driven subclassification of speech sound disorders in preschool children.

Authors:  Jennell C Vick; Thomas F Campbell; Lawrence D Shriberg; Jordan R Green; Klaus Truemper; Heather Leavy Rusiewicz; Christopher A Moore
Journal:  J Speech Lang Hear Res       Date:  2014-12       Impact factor: 2.297

7.  Effects of early language, speech, and cognition on later reading: a mediation analysis.

Authors:  Vanessa N Durand; Irene M Loe; Jason D Yeatman; Heidi M Feldman
Journal:  Front Psychol       Date:  2013-09-03
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.