標題: Power and sample size calculations for multivariate linear models with random explanatory variables
作者: Shieh, G
管理科學系
Department of Management Science
關鍵字: MANCOVA;MANOVA;multivariate regression;noncentral F distribution
公開日期: 1-六月-2005
摘要: This article considers the problem of power and sample size calculations for normal outcomes within the framework of multivariate linear models. The emphasis is placed on the practical situation that not only the values of response variables for each subject are just available after the observations are made, but also the levels of explanatory variables cannot be predetermined before data collection. Using analytic justification, it is shown that the proposed methods extend the existing approaches to accommodate the extra variability and arbitrary configurations of the explanatory variables. The major modification involves the noncentrality parameters associated with the F approximations to the transformations of Wilks likelihood ratio, Pillai trace and Hotelling-Lawley trace statistics. A treatment of multivariate analysis of covariance models is employed to demonstrate the distinct features of the proposed extension. Monte Carlo simulation studies are conducted to assess the accuracy using a child's intellectual development model. The results update and expand upon current work in the literature.
URI: http://dx.doi.org/10.1007/s11336-003-1094-0
http://hdl.handle.net/11536/13599
ISSN: 0033-3123
DOI: 10.1007/s11336-003-1094-0
期刊: PSYCHOMETRIKA
Volume: 70
Issue: 2
起始頁: 347
結束頁: 358
顯示於類別:期刊論文


文件中的檔案:

  1. 000235235100007.pdf