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。

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.