Estimating Model-Adjusted Risks, Risk Differences, and Risk Ratios From Complex Survey Data
Estimating Model-Adjusted Risks, Risk Differences, and Risk Ratios From Complex Survey Data
复制标题
DOI：
10.1093/aje/kwp440
复制
发表时间：
2010-03-01
影响因子：
5
通讯作者：
Brogan, Donna J.
中科院分区：
文献类型：
--
作者：
Bieler, Gayle S.;Brown, G. Gordon;Brogan, Donna J.
在回归设置中，人们对估计和推断风险或患病率比率和差异而不是比值比越来越感兴趣。最近的出版物显示了SAS （SAS Institute Inc., Cary, North Carolina）的GENMOD程序如何在非基于人群的研究中用于估计这些参数。在本文中，作者展示了如何从复杂样本调查设置的逻辑回归模型中直接获得模型调整后的风险、风险差异和风险比估计，从而产生基于人群的推断。复杂的抽样调查设计通常涉及一些加权、分层、多阶段抽样、聚类和有限人口调整的组合。模型调整后的风险、风险差异和风险比的点估计是由拟合的逻辑回归模型中的平均边际预测获得的。该模型既可以包含连续协变量，也可以包含分类协变量，以及交互项。作者使用SUDAAN软件包（北卡罗来纳州三角研究所，三角研究公园）获得点估计，标准误差（通过线性化或复制方法），置信区间和P值的参数和感兴趣的对比。本文使用2006年全国健康访谈调查的数据来说明这些概念。
There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted risks, risk differences, and risk ratio estimates can be obtained directly from logistic regression models in the complex sample survey setting to yield population-based inferences. Complex sample survey designs typically involve some combination of weighting, stratification, multistage sampling, clustering, and perhaps finite population adjustments. Point estimates of model-adjusted risks, risk differences, and risk ratios are obtained from average marginal predictions in the fitted logistic regression model. The model can contain both continuous and categorical covariates, as well as interaction terms. The authors use the SUDAAN software package (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates, standard errors (via linearization or a replication method), confidence intervals, and P values for the parameters and contrasts of interest. Data from the 2006 National Health Interview Survey are used to illustrate these concepts.