Semiparametric analysis of longitudinal zero-inflated count data

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. Citation: Yao P, Liu X (2013) Semiparametric Analysis of Longitudinal Zero-inflated Count Data with Applications to Instrumental Activities of Daily Living. J Biomet Biostat 4: 172. doi:10.4172/2155-6180.1000172 J Biomet Biostat ISSN: 2155-6180 JBMBS, an open access journal Page 2 of 4 Volume 4 • Issue 4 • 1000172 Statistical Models and Estimation The zero-inflated Poisson model The ZIP model includes two parts of parameters: one for zero inflated measures and the other for repeated Poisson counts. Let response vectors 1 ( ,..., ) , = T T T N Y Y Y where 1 ( ,..., ) = T T T i i iT Y Y Y and the response Yij denote the count for i th subject at time j, i=1,..., N, j=1,..., T. The probability of an excess zero is denoted by πij , 0 ≤ πij ≤ 1. Here we adopt ZIP regression models introduced by Lambert [14] ( ) ( ) ( ) 1 , 0; | , 1 , 0, ! μ