Nonparametric Models and Methods for Analysis of Covariance in Social Sciences Research

社会科学研究中协方差分析的非参数模型和方法

• 批准号: 9709891
• 负责人: Michael Akritas
• 金额: $ 16.47万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9709891&HistoricalAwards=false
• 关键词: Nonparametric; Models; Methods; Analysis; Covariance

The objective of this research is to develop a family of fully nonparametric statistical methods and associated software for use in social sciences research. These procedures require minimal modeling assumptions, possess desirable invariance properties, will allow the analysis of all types of ordinal data (continuous, ordered categorical, and data with ties), and will also permit the data to be either independent or dependent (as, for example, in longitudinal studies). The software developed will consist of SAS macros and S-plus functions which will be made available to researchers in the social sciences through several World-Wide-Web sites.

本研究的目的是开发一个家庭的完全非参数统计方法和相关的软件用于社会科学研究。 这些程序需要最少的建模假设，具有理想的不变性，将允许分析所有类型的有序数据（连续，有序分类，和数据与领带），也将允许数据是独立的或依赖的（如，例如，在纵向研究）。 开发的软件将由SAS宏和S-plus功能组成，这些功能将通过多个万维网网站提供给社会科学研究人员。