医学多变量重复观测资料的随机系数模型-论文论文发表 Keywords】 repeated measures; random coefficients model; multivariate statistics [gap=339]关键词】 重复观测;随机系数模型;多元统计学
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随机系数AR模型 stochastic coefficient AR model
随机系数回归模型 random-coefficient regression models
随机系数离散选择模型 random coefficient discrete choice model ; RCM
方法通过两水平随机系数模型以及顺序效应的拟合，估计处理效应的大小及其在个体间的变异。
Methods Fitting two-level random coefficient model and sequence effect to estimate the treatment effect and its variation between individuals.
结论：多变量随机系数模型可有效地进行多变量重复观测数据的动态变化趋势分析以及随机效应分析。
CONCLUSION: multivariate random coefficients model can effectively analyze the dynamic change trend and random effects of multivariate repeated measures data in medical research.
讨论误差相关下半变系数模型的随机约束估计。
The random constrained estimation of semi-varying coefficient models with co-relational errors are discussed in this paper.
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