This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Negative binomial mixed models for analysis of stuttering rates

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Jones, Mark
Dobson, Annette
Onslow, Mark
Carey, Brenda
Abstract

Stuttering involves disruptions to normal verbal behavior. The rate that these disruptions occur within individuals who stutter varies across time and also with speaking situation. Therefore multiple samples of speech are commonly taken from individuals, in an attempt to obtain a realistic estimate of the severity of their condition. Stuttering rates are commonly reported as the proportion of syllables stuttered. Traditionally, general linear models have been used to analyze and compare stuttering rates. However, the distribution of this type of data is not normal, the duration of the individual speech samples is not usually taken into account, and repeated measurements on individuals are often aggregated prior to analysis. We propose that these issues can be resolved by using a negative binomial mixed model approach. In this paper, we argue why this is sensible and then show that the model is practical to implement, drawing on data from two randomized controlled trials of interventions for treatment of stuttering. We also show how to estimate sample size for our proposed model based on a negative binomial distribution.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/B6V8V-4WVK4T7-3/2/973c8c68712a7224ba90dc547fff101d
File Format:
File Function:
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 53 (2009)
Issue (Month): 12 (October)
Pages: 4590-4600
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4590-4600

Contact details of provider:
Web page: http://www.elsevier.com/locate/csda

For technical questions regarding this item, or to correct its listing, contact: (Heidi Boesdal).

Related research
Keywords:

Statistics
Access and download statistics

Did you know? RePEc encourages publishers to make their bibliographic data freely available to the public.

This page was last updated on 2009-12-3.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.