Combining information from independent surveys, small area estimation of complex parameters, analysis of complex survey data

基于概率抽样的抽样调查被广泛用于提供关于各种重要主题的可靠的当前统计数据。可变性测量（标准误差和置信区间）用于评估样本统计的质量。调查越来越多地被用于提供小范围的统计数据，例如县贫困学龄儿童的估计，这些数据在制定政策和项目、资金分配和营销决策中都是必需的。结合独立调查的信息（数据融合）来获得有效的估计和研究变量之间的关系，并不是所有的变量都在同一调查中被观察到，已经受到了广泛的关注。社会和卫生科学家及其他人员使用调查数据来研究各种关系和检验有关假设，例如加拿大全国公共卫生调查的纵向数据。我的研究计划将集中在上述所有当前感兴趣的主题上。特别是，我计划研究以下问题：(a)我在小区域估计方面做了大量的工作，我2003年出版的Wiley书已经成为研究人员和用户关于基于模型的方法的标准参考，即使在区域内的样本量很小的情况下，也可以得出可靠的估计。我建议继续研究基于模型的方法，特别是用于估计复杂的小区域参数，例如世界银行在发展中国家使用的贫困指标，使用现实模型和最佳估计方法。(b)多级模型通常用于分析多阶段抽样的数据，例如学校样本（第2级）和学校内学生样本（第1级）。我计划研究我最近开发的一种新方法的理论性质和扩展，这种方法可以得出有效的推论并提供统一的方法。(c)我最近关于综合独立调查资料的工作提供了估计总数的有效方法。扩展处理更复杂的参数，如回归系数和缺失数据将被研究。

Sample surveys, based on probability sampling, are widely used to provide reliable current statistics on a variety of important topics. Measures of variability (standard errors and confidence intervals) are used to assess the quality of the sample statistics. Surveys are increasingly being used to provide small area statistics, such as county estimates of poor school-age children, that are needed in formulating policies and programs, allocation of funds and marketing decisions. Combining information from independent surveys (data fusion) to obtain efficent estimates and study relationships between varaibles not all observed in the same survey has received much attention. Survey data are used by social and health scientists and others to study realtionships and to test hypotheses of interest, e.g, longitudinal data from the National Public Health Survey of Canada. My research program will focus on all the above topics of current interest. In particular, I plan to study the following problems among others:(a) I have done extensive work on small area estimation and my 2003 Wiley book has become a standard reference to researchers and users on model-based methods that can lead to reliable estimates even when the sample sizes are small within areas. I propose to continue my work on model-based methods, especially for estimating complex small area parameters such as poverty measures used by the World Bank in developing countries, using realistic models and optimal estimation methods. (b) Multi-level models are often used to analyse data from multistage sampling, e.g. sample of schools (level 2) and students (level 1) within schools. I plan to study the theoretical properties and extensions of a new method I have recently developed that leads to valid inferences and provides a unified approach. (c) My recent work on combining information from independent surveys provides efficient methods of estimating totals. Extensions to handle more complex parameters such as regression coefficeints, and missing data will be studied.