標題: General multivariate linear models for longitudinal studies
作者: Shieh, GW
管理科學系
Department of Management Science
關鍵字: doubly multivariate linear models;GMANOVA;growth curve models;MANOVA;pooled time series and cross-sectional data;repeated measures design;seemingly unrelated regression models;time-varying covariates
公開日期: 2000
摘要: Longitudinal studies occur frequently in many different disciplines. To fully utilize the potential value of the information contained in a longitudinal data, various multivariate linear models have been proposed. The methodology and analysis are somewhat unique in their own ways and their relationships are not well understood and presented. This article describes a general multivariate linear model for longitudinal data and attempts to provide a constructive formulation of the components in the mean response profile. The objective is to point out the extension and connections of some well-known models that have been obscured by different areas of application. More importantly, the model is expressed in a unified regression form from the subject matter considerations. Such an approach is simpler and more intuitive than other ways to modeling and parameter estimation. As a consequence the analyses of the general class of models for longitudinal data can be easily implemented with standard software.
URI: http://hdl.handle.net/11536/30881
http://dx.doi.org/10.1080/03610920008832512
ISSN: 0361-0926
DOI: 10.1080/03610920008832512
期刊: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Volume: 29
Issue: 4
起始頁: 735
結束頁: 753
顯示於類別:期刊論文


文件中的檔案:

  1. 000086299800002.pdf