alexa Semiparametric Analysis of Longitudinal Zero-inflated Count Dat a with Applications to Instrumental Activities of Daily Living | OMICS International
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
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Research Article

Semiparametric Analysis of Longitudinal Zero-inflated Count Dat a with Applications to Instrumental Activities of Daily Living

Ping Yao1* and Xiaohong Liu2

1Public Health and Health Education Program, School of Nursing and Health Studies, Northern Illinois University, Wirtz Hall 260, DeKalb, IL, 60115, USA

2Division of Statistics, Northern Illinois University, Dekalb, IL, 60115, USA

*Corresponding Author:
Ping Yao
Public Health and Health Education Program
School of Nursing and Health Studies
Northern Illinois University
Wirtz Hall 260, DeKalb, IL, 60115, USA
Tel: 815-753-0853
Fax: 815-753-5406
E-mail: [email protected]

Received Date: July 24, 2013; Accepted Date: August 28, 2013; Published Date: August 30, 2013

Citation: Yao P, Liu X (2013) Semiparametric Analysis of Longitudinal Zeroinflated Count Data with Applications to Instrumental Activities of Daily Living. J Biomet Biostat 4:172. doi:10.4172/2155-6180.1000172

Copyright: © 2013 Yao P, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: The instrumental activities of daily living (IADLs) are important index of physical functioning in older adult studies. These count outcomes with a large proportion of zeros are often collected in longitudinal studies. Data were from the Hispanic Established Population for Epidemiological Study of the Elderly (HEPESE), a four wave (seven years) longitudinal study of community-dwelling elderly Mexican-Americans. There were excess zeros IADLs observed during follow-up.
Methods: We present semiparametric zero-inflated Poisson (ZIP) and hurdle model with random effects to evaluate IADLs in the context of excess zeros. Results: Age, education, household income, marital status, smoking, cognitive functioning and prescription medication use were not significantly associated with IADLs. The counts of IADLs changed with age nonlinearly.
Conclusions: zero-inflated Poisson (ZIP) and hurdle model with random effect fits the IADLs counts with excess zeros in longitudinal studies.

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