METHODS FOR ANALYZING COMPLEX HEALTH SURVEY DATA

家庭调查的数据来自于以下人员的聚类样本： 通常以差别费率进行选择。抽样的这几个方面 导致观察结果的非独立性和不平等权重 应在分析阶段予以考虑。健康调查数据为 通过长期随访，广泛用于队列研究 通过提供群体控制进行样本、病例对照研究，以及 横断面研究。 研究已扩展到扩展各种统计数据 应用于调查数据的方法。一些主要领域 研究情况如下： - 为复杂的情况开发了比例风险回归分析 具有时间依赖性协变量和左截断时间的健康调查数据 到事件。这些方法被应用到了第一次的后续工作中 全国健康和营养检查调查。 - 图形方法被推广到解决以下问题的调查数据 样本加权和许多观察结果 全国健康调查。 - 开发了用于估计超总体方差的方法 调查数据。对标准方差估计量的修正提供 对超级总体方差的一致估计。 - 计算小样本置信区间的方法 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。 对于每个领域，手稿要么正在提交，要么正在处理中 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.