Analysis of survery data

研究建议涉及观测在时间或空间上的关联性和相关性的统计建模，特别强调调查数据和调查方法。 我建议在分析复杂调查数据的三个方面开展工作。第一个主题是事件时间的联合分布和空间分析的密度估计;当我们有兴趣评估一种类型的事件是否可能引发另一种事件时，前者是相关的，后者将适用于疾病发病率的空间分布的可视化。 第二个主题是估计多层次模型，其中解释变量在一个以上的聚合水平被用来模拟响应，因为这种建模越来越广泛地使用，rescue方法，允许复杂的抽样设计估计方差分量，并可以提供给分析师，将进行探讨。 最后，我将研究层次模型在调查数据分析中解释人口异质性的应用，特别是在跨文化调查方法中的应用。 在国际调查的背景下，社会科学家和卫生科学家对这一主题非常感兴趣。

The research proposal concerns the statistical modelling of association and dependence among observations in time or space, with particular emphasis on survey data and survey methodology. I am proposing work on three aspects of the analysis of complex survey data. The first topic is that of density estimation for the joint distribution of event times and for spatial analysis; the former is relevant when we are interested in assessing whether one type of event might trigger another, and the latter will be applicable to the visualization of spatial distributions of disease incidence. The second topic is estimation in multilevel models, wherein explanatory variables at more than one level of aggregation are used to model responses; since this kind of modeling is increasingly widely used, resampling methods which allow for the complex sampling design in estimating components of variance, and which can be made available to analysts, will be explored. Finally, I will study applications of hierarchical models to account for population heterogeneity in the analysis of survey data, with particular application to cross-cultural survey methods. This topic is of great interest to social scientists and health scientists in the context of international surveys.