ABSTRACT

In this paper, we propose and explore a novel semiparametric approach to analyzing longitudinal count data. We address the issue of missingness in longitudinal data and propose a weighted generalized estimations equations approach to fitting marginal mean response models for count responses with dropouts. Also, we investigate a spline regression approach to approximating the curvilinear relationship between the mean response and covariates. The asymptotic properties of the proposed estimators are studied in some detail. The empirical properties of the estimators are investigated using Monte Carlo simulations. An application is also provided using actual survey data obtained from the Health and Retirement Study (HRS).

摘要

在本文中，我们提出并探索了一种新的半参数方法来分析纵向计数数据。我们解决了纵向数据中的缺失问题，并提出了一种加权广义估计方程方法来拟合边缘平均响应模型，以适应具有丢失的计数响应。此外，我们研究了一种样条回归方法来近似平均响应和协变量之间的曲线关系。对所提出的估计量的渐近性质进行了一些详细的研究。使用蒙特卡罗模拟研究估计量的经验特性。还使用从健康和退休研究 (HRS) 获得的实际调查数据提供应用程序。