METHODS FOR ANALYZING REPEATED CATEGORICAL DATA

分析重复分类数据的方法

• 批准号: 3460376
• 负责人: Stuart R. Lipsitz
• 金额: $ 11.19万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-05-06 至 1997-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3460376
• 关键词: computer data analysis; computer program /software; computer simulation; computer system hardware; mainframe computers; mathematical model; method development; statistics /biometry

Repeated measures studies arise in all areas of Public Health, and the responses are often categorical (such as sick or well), and not continuous (such as blood pressure). In repeated measures studies, the basic sampling unit is a group or cluster of subjects; a measurement is made on each subject within the cluster. For example, in a toxicological study, the cluster is a litter, and the fetuses or newborns are the subjects within the litter; in a longitudinal study of health effects of air pollution, the cluster is a person, and the repeated measures are the responses at the different times. Repeated measures studies present some quite unique problems, especially when the response is categorical, and it is these problems on which this proposal is focused. The longterm research objectives to develop new methods for analyzing repeated categorical responses as well as to make the old and new methods more accessible to the non-statistician. The proposed methods address a variety of issues that are relevant to repeated measures studies in epidemiology, clinical trials, and environmental science. Since small samples can invalidate the asymptotic approximations that have been proposed for analyzing repeated measures data, methods appropriate for small samples will be explored. Because the jackknife has been shown to provide consistent estimates of the variance of regression parameter estimates in longitudinal studies, we propose to use the jackknife in a wider range of problems, including providing an estimate of the variance of the estimated correlation parameters. In the simplest kind of repeated measures study with no covariates, investigators are often interested in measuring agreement among a set of repeated binary (or polychotomous) measurements on individuals; the third goal is to develop simple methods for estimating measures of agreement. A fourth goal is to extend the methods for analyzing repeated binary responses to analyze also repeated polychotomous responses, and in particular, repeated ordinal responses. A final goal is to develop methods for calculating the sample size (of clusters and subjects within clusters) necessary to obtain a given level of precision.

公共卫生的所有领域都出现了重复措施研究，并且 反应通常是明确的（例如生病或健康），而不是连续的 （如血压）。 在重复测量研究中，基本抽样 单元是一组或一组主题；对每个进行测量 簇内的主题。 例如，在毒理学研究中， cluster 是一窝幼崽，胎儿或新生儿是其中的对象 垃圾；在一项关于空气污染对健康影响的纵向研究中， 簇是一个人，重复测量是在该处的响应 不同的时间。 重复测量研究提出了一些非常独特的 问题，特别是当响应是明确的时，而正是这些 本提案所关注的问题。 长期研究 目标是开发新方法来分析重复的分类 响应以及使新旧方法更容易为人们所接受 非统计学家。 所提出的方法解决了与以下相关的各种问题 流行病学、临床试验和重复测量研究 环境科学。 由于小样本可能会使渐近无效 为分析重复测量而提出的近似值 数据，将探索适合小样本的方法。 因为 Jackknife 已被证明可以提供一致的方差估计 纵向研究中的回归参数估计，我们建议使用 折刀处理更广泛的问题，包括提供估计 估计相关参数的方差。 在最简单的 一种没有协变量的重复测量研究，研究人员经常 有兴趣测量一组重复的二进制文件之间的一致性（或 多分类）对个体的测量；第三个目标是发展 估计一致性度量的简单方法。 第四个目标是 扩展分析重复二元响应的方法来分析 重复的多分类反应，特别是重复的序数反应 回应。 最终目标是开发计算样本的方法 获得给定值所需的（聚类和聚类内的主题）大小 精度水平。