Conclusion Mixed linear model can be used to analyze repeated measurement data in single-sample.
结论混合线性模型可以有效地、全面地分析单样本重复测量资料。
ObjectiveTo explore statistical approaches to analyzing factorial designed repeated measurement data.
目的探讨析因设计重复测量资料的统计分析方法。
Objective to explore statistical approaches to analyzing factorial designed repeated measurement data.
摘要目的探讨析因设计重复测量资料的统计分析方法。
Objective To study the nonlinear analysis methods for repeated measurement data, implement parameter estimate in PPK by NLMIXED procedure in SAS soft.
目的探讨重复测量资料非线性分析技术、SAS软件NLMIXED过程及在群体药动学的应用。
According the characteristics of the bivariate repeated measurement data, using the MIXED procedure of SAS software to fit linear mixed effects model.
目的：通过混合效应线性模型与单因素方差分析在重复测量资料中的应用比较，旨在说明两方法在处理重复测量资料时的应用特点。
In modelling the bivariate repeated measurement data, using the PROC MIXED of SAS, the correlation between data could be cut into two parts: between variables and between multiple measurements.
在双反应变量重复测量资料模型构建过程中，使用SAS的MIXED过程，将重复测量数据间的相关性分为变量之间的相关与重复测量个体值之间的相关两部分。
This paper introduces a general methodology for the analysis of repeated measurement of categorical data. A clinical example is illustrated.
本文介绍分析重复测量分类数据的一般统计方法，并用临床资料进行实例分析。
This paper introduces a general methodology for the analysis of repeated measurement of categorical data. A clinical example is illustrated.
本文介绍分析重复测量分类数据的一般统计方法，并用临床资料进行实例分析。
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