...
首页> 外文期刊>Biometrika >Analysing ordinal longitudinal survey data: Generalised estimating equations approach
【24h】

Analysing ordinal longitudinal survey data: Generalised estimating equations approach

机译:分析有序纵向调查数据:广义估计方程法

获取原文
获取原文并翻译 | 示例

摘要

Longitudinal survey data may comprise ordinal polytomous repeated observations and a set of multidimensional covariates for a large number of individuals. One of the main goals of the longitudinal survey is then to describe the marginal expectation of the ordinal polytomous outcome variable as a function of the covariates while accounting for the structural as well as longitudinal correlations. The structural correlations come from the polytomous nature of the response variable, and the longitudinal correlations from the repetition of the polytomous responses over time. In this paper we develop a generalised estimating equations approach based on autocorrelation structure to deal with multivariate polytomous longitudinal survey data, the univariate and bivariate analyses being special cases. The regression estimators are shown to be consistent for the corresponding regression parameters. The methods are illustrated by using the Survey of Labour and Income Dynamics data from Statistics Canada. [References: 14]
机译:纵向调查数据可以包括针对多个个体的有序多角度重复观察和一组多维协变量。纵向调查的主要目标之一是描述有序的多结局结果变量作为协变量的函数的边际期望,同时考虑结构和纵向相关性。结构相关性来自于响应变量的多态性,而纵向相关性则来自于随着时间的推移多态性响应的重复。在本文中,我们开发了一种基于自相关结构的广义估计方程方法来处理多变量多纵向调查数据,单变量和双变量分析是特殊情况。回归估计值显示为对应的回归参数一致。通过使用加拿大统计局的劳动力和收入动态调查数据说明了这些方法。 [参考:14]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号