METHODS FOR ANALYZING LONGITUDINAL DATA

纵向数据分析方法

基本信息

批准号：
2130180
负责人：
CHARLES J KOWALSKI
金额：
$ 12.75万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
1988
资助国家：
美国
起止时间：
1988-07-01 至 1995-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/2130180
关键词：
automated medical record system cephalometry child physical development computer data analysis computer human interaction computer program /software computer simulation computer system design /evaluation dental research growth /development human data information retrieval longitudinal human study publications statistics /biometry

项目摘要

It is generally acknowledged that longitudinal rather than cross-sectional data provide the most information on growth and other time-dependent phenomena. This recognition in the area of craniofacial biology has led to the collection of excellent longitudinal data sets that contain valuable information on normal, abnormal, and altered growth and development in humans and other primates. Nevertheless, with few exceptions, appropriate statistical methods which adequately account for the covariance structure of such data sets have not been employed in their analysis. Apart from the programs which were produced during the first three years of this project, methods that are accessible and readily usable by the biomedical community are unavailable. Despite the formulation of mathematical models which are suitable for the analysis of longitudinal data (see, eg., the reviews in Kowalski and Guire, 1974; Goldstein, 1979; Guire and Kowalski, 1979; Marubini and Milani, 1986), implementation has lagged far behind theoretical development. The purpose of this research is to systematically compare available methods for longitudinal data analysis and implement the most suitable ones using the matrix algebra programming language, GAUSS (Edlefson and Jones, 1985). The goal is to develop computer programs that can be used easily by basic and clinical scientists to facilitate meaningful descriptions and comparisons of growth patterns in human and other primate populations. An integrated system of user-friendly programs will be developed and made available to the biomedical research community. These GAUSS programs will be in a stand-alone format that is easy to install and use -- no additional software is required. They will be thoroughly documented and detailed instructions for installing and running them will be provided. These menu-driven programs elicit from the user all of the information required to perform the analysis, ie., the dimensions and format of his/her data set. Articles issuing from this project will be written for investigators with only a basic understanding of statistics and will describe the conceptual bases, practical applications and use of the methods and programs. Instructions for program installation and use will be provided to, and updated for, all those requesting our programs. By providing easy-to-use tools for generating accurate descriptions of human growth, this project will contribute to improved health care in the areas of orthodontics, oral and maxillofacial surgery, cleft-lip and palate rehabilitation, and pediatrics.

人们普遍认为纵向而不是横截面数据提供了有关增长和其他的最多信息时间依赖现象。这种在颅面领域的认可生物学导致收集出色的纵向数据集其中包含有关正常，异常和变化的有价值的信息和人类和其他灵长类动物的发展。然而，很少有例外，适当说明的适当统计方法此类数据集的协方差结构尚未使用他们的分析。除了在该项目的前三年，可访问的方法生物医学界很容易使用。尽管有适合分析的数学模型的配方纵向数据（例如，参见Kowalski and Guire的评论，1974年；戈德斯坦，1979年； Guire and Kowalski，1979年； Marubini和Milani，1986年），实施远远落后于理论发展。这项研究的目的是系统地比较可用的方法用于纵向数据分析和实施最多的方法使用矩阵代数编程语言的合适的（Edlefson和Jones，1985）。目标是开发计算机程序基本和临床科学家可以轻松地使用它来促进人类和其他灵长类动物。用户友好的集成系统计划将开发并提供给生物医学研究社区。这些高斯程序将以独立格式为易于安装和使用 - 不需要其他软件。他们会的彻底记录了安装和详细的说明将提供运行它们。这些菜单驱动的程序从用户执行分析所需的所有信息，即他/她的数据集的尺寸和格式。该项目发行的文章将为对统计数据的基本理解的调查人员将描述概念基础，实际应用和使用方法和程序。程序安装和使用的说明将向所有请求我们计划的人提供并更新。经过提供易于使用的工具来生成人类的准确描述增长，该项目将有助于改善该领域的医疗保健正畸，口腔和上颌面手术，唇裂和口感康复和儿科。