General class of covariance structures for two or more repeated factors in longitudinal data analysis
DOI: 10.1080/03610929408831436
关键词:
摘要: The main difficulty in parametric analysis of longitudinal data lies specifying covariance structure. Several structures, which usually reflect one series measurements collected over time, have been presented the literature. However there is a lack literature on structures designed for repeated measures specified by more than factor. In this paper new, general method modelling structure based Kronecker product underlying factor specific profiles presented. has an attractive interpretation terms independent contribution to overall within subject and can be easily adapted standard software.
sci-hub.se 参考文章(5)
Peter McCullagh, Tensor Methods in Statistics ,(1987)
Russ Wolfinger, Randy Tobias, John Sall, Computing Gaussian likelihoods and their derivatives for general linear mixed models SIAM Journal on Scientific Computing. ,vol. 15, pp. 1294- 1310 ,(1994) , 10.1137/0915079
Robert I. Jennrich, Mark D. Schluchter, Unbalanced repeated-measures models with structured covariance matrices Biometrics. ,vol. 42, pp. 805- 820 ,(1986) , 10.2307/2530695
KUNG-YEE LIANG, SCOTT L. ZEGER, Longitudinal data analysis using generalized linear models Biometrika. ,vol. 73, pp. 13- 22 ,(1986) , 10.1093/BIOMET/73.1.13
Calyampudi Radhakrishna Rao, Linear statistical inference and its applications ,(1965)