Statistical inference in zero-inflated random effects models with missing data

缺失数据的零膨胀随机效应模型的统计推断

• 批准号: RGPIN-2016-04322
• 负责人: Yan, Guohua
• 金额: $ 1.09万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=614987
• 关键词: Statistical; inference; zero; inflated; random

Correlated data are common in a variety of disciplines such as biological, ecological, health and medical studies. Data are correlated due to, for example, repeated-measures, or a nest design, or a natural hierarchy of units. Random effects models (or mixed models or hierarchical models) are widely used to analyse these data, in which random effects are introduced to account for correlation within a hierarchy. For example, in medical longitudinal studies, random effects are often used to model the heterogeneity between subjects. These random effects characterize the varying susceptibilities of subjects to certain diseases. In modelling correlated data, it is common to encounter a large number of zeros. For example, in studies of insurance claims, a large number of people will have zero claims during a certain period of time. In addition, some data may be missing for certain reasons. The presence and zero-inflation and missing data poses challenges to data analysis. In the proposed research I will develop efficient data analysis methods for random effects models with the presence of zero-inflation and missing data. I will also pursue variable selection and model assessment in this context. As these data complexities are common in many disciplines, the methods to be developed will be widely applicable. The methods will be easily accessible to applied researchers through worked examples and user-friendly packages.

相关数据在生物、生态、健康和医学研究等各种学科中都很常见。数据是相互关联的，例如，由于重复测量，或嵌套设计，或单位的自然层次结构。随机效应模型（或混合模型或层次模型）被广泛用于分析这些数据，其中引入随机效应来解释层次内的相关性。例如，在医学纵向研究中，经常使用随机效应来模拟受试者之间的异质性。这些随机效应表征了受试者对某些疾病的不同易感性。