METHODS FOR ANALYZING COMPLEX HEALTH SURVEY DATA

来自家庭调查的数据来自于 经常以不同的比率被挑选出来的人。 抽样的这些方面导致了非独立性和 不同权重的意见应该是 在分析阶段进行了考虑。健康调查数据 在长期的队列研究中被广泛使用 样本的后续研究，病例对照研究，通过提供 人口控制和横断面研究。 已经进行了研究，以扩展各种 应用于调查数据的统计方法。一些人 主要研究领域如下： -发展了比例风险回归分析 对于具有时间依赖关系的复杂健康调查数据 协变量和事件的左侧截断时间。这些方法 应用于第一次全民健康的随访 和营养检查调查。 -图表方法被推广到调查数据，这些数据 解决了样本加权和大量的 在许多国家健康调查中发现的观察结果。 -制定了估计超级人口的方法 与调查数据的差异。对标准的更正 方差估计器提供一致的估计 超大种群差异。 -估计分组数据的百分位数的方法 对调查进行了调查。 -对调整后的预算进行了研究 广义线性和比例关系的处理方法 风险回归模型。 对于这些领域中的每一个领域，手稿都在 提交的或正在书写的。

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 estimating percentiles for grouped data from surveys were investigated. - 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.