METHODS FOR ANALYZING COMPLEX HEALTH SURVEY DATA

住户调查的数据来自下列人员的集群抽样： 通常以不同的比率选择。抽样的这些方面 导致观察的非独立性和不平等权重， 应该在分析阶段考虑。健康调查数据是 通过长期随访，广泛用于队列研究。 通过提供人群对照进行样本病例对照研究，以及 横截面研究。 已经进行了研究，以扩展各种统计数据， 应用于调查数据的方法。一些主要领域 研究如下： - 比例风险回归分析是复杂的 具有时间相关协变量和左截断时间的健康调查数据 事件。这些方法被应用于第一次 全国健康和营养检查调查。 - 图形方法被推广到调查数据， 样本加权和许多国家发现的大量观测结果 国家健康调查。 - 方法被开发用于估计超总体方差， 调查数据对标准方差估计量的修正提供了 超总体方差的一致估计。 - 小样本置信区间的计算方法 正在进行调查。 - 对调整后的治疗平均值的估计进行了研究 广义线性和比例风险回归模型。 对于这些领域中的每一个，手稿要么正在提交，要么正在提交。 写着

Data from household surveys are from clustered samples of persons who are often selected at differential rates. These aspects of the sampling result in nonindependence and unequal weighting of the observations that should be considered during the analysis stage. Health survey data are used extensively in cohort studies through long term followup of the sample, case-control studies by providing population controls, and cross-sectional studies. Research has been conducted into extending a variety of statistical methods for application to survey data. Some of the major areas of research are as follows: - Proportional hazard regression analysis was developed for complex health survey data with time dependent covariates and left truncated time to event. These methods were applied to the followup of the First National Health and Nutrition Examination Survey. - Graphical methods were generalized to survey data which address the sample weighting and the large number of observations found in many national health surveys. - Methods were developed for estimating super-population variances from survey data. Corrections to standard variance estimators provide consistent estimates for super-population variances. - Methods for computing confidence intervals for small samples from surveys are being developed. - Research was conducted on the estimation of adjusted treatment means for generalized linear and proportional hazard regression models. For each of these areas, manuscripts are either under submission or being written.