A partially linear additive model for clustered proportion data.
A partially linear additive model for clustered proportion data.
复制标题
DOI：
10.1002/sim.7573
复制
发表时间：
2018-03-15
影响因子：
2
通讯作者：
Bandyopadhyay D
中科院分区：
文献类型：
--
作者：
Zhao W;Lian H;Bandyopadhyay D
Proportion data with support lying in the interval [0,1] are a commonplace in various domains of medicine and public health. When this data are available as clusters, it is important to correctly incorporate the within-cluster correlation to improve the estimation efficiency while conducting regression-based risk evaluation. Furthermore, covariates may exhibit a non-linear relationship with the (proportion) responses while quantifying disease status. As an alternative to various existing classical methods for modeling proportion data (such as augmented Beta regression, etc) that utilizes maximum likelihood, or generalized estimating equations, we develop a partially linear additive model based on the quadratic inference function. Relying on quasi-likelihood estimation techniques and polynomial splines approximation for unknown nonparametric functions, we obtain the estimators for both parametric part and nonparametric part of our model, and study their large sample theoretical properties. We illustrate the advantages and usefulness of our proposition over other alternatives via extensive simulation studies, and application to a real dataset from a clinical periodontal study.
登录
查看更多内容
影响因子：
4.3
作者：
Fernandes JK;Wiegand RE;Salinas CF;Grossi SG;Sanders JJ;Lopes-Virella MF;Slate EH
通讯作者：
Slate EH
影响因子：
1
作者：
Pereira, Gustavo H. A.;Botter, Denise A.;Sandoval, Monica C.
通讯作者：
Sandoval, Monica C.
影响因子：
1
作者：
Qiu, Zhenguo;Song, Peter X. -K.;Tan, Ming
通讯作者：
Tan, Ming
影响因子：
1
作者：
Kieschnick, R;McCullough, BD
通讯作者：
McCullough, BD
影响因子：
1.6
作者：
He, XM;Shi, PD
通讯作者：
Shi, PD