Models for correlated discrete data, with extension and application to small area estimation

相关离散数据模型，可扩展并应用于小区域估计

• 批准号: 193998-2011
• 负责人: Farrell, Patrick
• 金额: $ 0.87万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=569725
• 关键词: Models; correlated; discrete; data; extension

The proposed research program focuses on the development and assessment of methods for estimating attributes associated with each of a number of small groups of individuals comprising a larger group. These small groups may be defined by a small geographic area within a larger one, or by classifying individuals in the large group according to some trait such as age. Attributes to be considered are counts and the proportion of individuals in each of the small groups that possess a particular characteristic. The development of approaches for the assessment of such attributes is motivated by studies on (1) infant mortality rates in various health areas in British Columbia, in which the annual number of deaths in each area are recorded over a number of years, and (2) the effect over a number of years of particulate matter on annual asthma hospitalization cases in a number of United States counties. Of interest in these motivating studies is the desire to determine accurate forecasts of the number of infant mortality/asthma hospitalization cases in future years. The methods developed must acknowledge that the data consist of observations collected over time for each health area/county, as well as their geographic proximity. Other applications on disease cases (measles, for example) will be considered, with a view towards forecasting trends and outbreaks of epidemics. Motivated by a seven year smoking prevention study conducted in elementary and high schools, methods will also be developed for the case where the attribute is a proportion of individuals that possess a particular characteristic. Approaches will be developed to forecast the proportion of smokers at each school at specific time points. These methods must acknowledge that the data comprise repeated observations over time, and the similarity in smoking behaviour of students at the same school. The proposed methods will also be applied to data from a cancer study, and to data reflecting wheezing status in children. Finally, the proposed methods will be extended to situations where information for a small group over time may be incomplete and some data are missing.

拟议的研究计划的重点是开发和评估的方法，估计与每个人组成一个较大的群体的一些小团体的属性。 这些小群体可以由较大地理区域内的小地理区域来定义，或者根据年龄等特征将大群体中的个体分类。 要考虑的属性是每个小群体中拥有特定特征的个体的数量和比例。 这些属性的评估方法的开发是由以下研究推动的：（1）不列颠哥伦比亚省各健康地区的婴儿死亡率，其中记录了若干年来每个地区的年度死亡人数;（2）若干年来颗粒物对美国若干县年度哮喘住院病例的影响。 在这些激励性研究中，感兴趣的是希望确定未来几年婴儿死亡/哮喘住院病例数量的准确预测。 所制定的方法必须承认，数据包括对每个卫生区/县长期收集的观察结果及其地理邻近性。 将考虑在疾病病例（例如麻疹）方面的其他应用，以期预测流行病的趋势和爆发。 在小学和高中进行的一项为期七年的吸烟预防研究的激励下，还将为属性是具有特定特征的个人比例的情况开发方法。 将制定方法来预测每个学校在特定时间点的吸烟者比例。 这些方法必须承认，数据包括随着时间的推移而重复的观察，以及同一学校学生吸烟行为的相似性。 所提出的方法也将应用于癌症研究的数据，以及反映儿童喘息状态的数据。 最后，所提出的方法将扩展到一个小群体的信息随着时间的推移可能是不完整的，一些数据丢失的情况。