Ciol Marcia A, Hoffman Jeanne M, Dudgeon Brian J, Shumway-Cook Anne, Yorkston Kathryn M, Chan Leighton
Department of Rehabilitation Medicine, University of Washington, Seattle, 98195, USA.
Arch Phys Med Rehabil. 2006 Feb;87(2):299-303. doi: 10.1016/j.apmr.2005.09.021.
Understanding the use of weights in the analysis of data from multistage surveys. Large national surveys are powerful tools with which to examine a variety of important rehabilitation-related issues and are currently the only feasible method to study disability trends over time. Because it is impractical to draw simple random samples from the entire United States, national surveys, such as the Medicare Current Beneficiary Survey (MCBS), select random samples of subgroups of a population. Thus, respondents may have unequal probabilities of being included in the survey, and weighting must be used in the analysis before the results may be generalized to the entire United States. Surveys such as the MCBS are rich sources of data for rehabilitation medicine, and it can be expected that more research will be conducted using these data sources. Statistical analysis of these data should account for the sampling scheme used in data collection. We review the principles involved in the design of multistage samples, the calculation of weights, and their use in the data analysis, focusing on their importance in the estimation of population values. Our objective is to help readers to understand and interpret results of research articles using this methodology. Examples using the MCBS data are provided to clarify the concepts presented in the article.
理解权重在多阶段调查数据分析中的应用。大型全国性调查是用以研究各类重要康复相关问题的有力工具，且是目前研究残疾随时间变化趋势的唯一可行方法。由于从整个美国抽取简单随机样本不切实际，诸如医疗保险当前受益人调查（MCBS）等全国性调查会选取人群亚组的随机样本。因此，受访者被纳入调查的概率可能不相等，在将结果推广至整个美国之前，分析时必须使用权重。像MCBS这样的调查是康复医学丰富的数据来源，可以预期会有更多研究使用这些数据源。对这些数据的统计分析应考虑数据收集时所采用的抽样方案。我们回顾多阶段样本设计、权重计算及其在数据分析中的应用所涉及的原理，重点关注它们在总体值估计中的重要性。我们的目标是帮助读者理解和解读使用此方法的研究文章的结果。文中提供了使用MCBS数据的示例以阐明文章中所呈现的概念。
