METHODS FOR ANALYZING COMPLEX HEALTH SURVEY DATA

来自家庭调查的数据来自于以下人群的整群抽样 通常以不同的比率选择。抽样的这些方面 导致观察结果的非独立性和权重不均 应在分析阶段考虑。健康调查数据为 通过长期随访，在队列研究中广泛使用 通过提供人口控制进行样本病例对照研究，以及 横断面研究。 已经进行了研究，以扩展各种统计数据 调查数据的应用方法。的一些主要领域 研究内容如下： -比例风险回归分析是为复杂的 具有时间依赖协变量和左截断时间的健康调查数据 去参加活动。这些方法被应用于第一次随访 全国健康与营养检查调查。 -图表方法被推广到调查数据，这些数据涉及 样本加权和大量观察发现在许多 全国健康调查。 -开发了估计超总体方差的方法 调查数据。对标准方差估计数的修正提供了 对超总体方差的一致估计。 -计算小样本的置信度区间的方法 调查正在进行中。 -对调整后的治疗手段的估计进行了研究 用于广义线性和比例风险回归模型。 对于这些领域中的每一个，手稿要么正在提交中，要么正在 写的。

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.