Multivariate Repeated-Measurement or Growth Curve Models with Multivariate Random-Effects Covariance Structure
研究了多元重复测量或增长曲线模型中个体随机效应协方差结构的估计、假设检验和同时置信区间，并通过两个数值例子演示方法。
Abstract The analysis of multiple-response, repeated-measurement or growth curve models with a multivariate random-effects covariance structure for individuals is considered. Results on estimation, hypothesis testing, and simultaneous confidence bounds for the parameters of the generalized linear model of Potthoff and Roy (1964) are derived for the multiple-response repeated-measurements model under the multivariate random-effects covariance structure. Two numerical examples are presented to illustrate these techniques.