结果通过固定效应与随机效应及对协方差矩阵的估计，使重复测量数据得以合理的分析。
Results Repeated measurement obtained reasonable results by the fixed and random effects along with efficient estimate of covariance matrix.
结论：由于重复测量数据间存在一定的自相关性和随机误差的多层次性，因而其分析方法有别于一般的统计分析方法。
Conclusion: Owing to correlation among repeated measures and its hierarchical error, the statistical analysis with repeated measures is different from other statistical approach.
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。
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.
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.
在医学研究的各个领域常会遇到重复测量资料的数据分析与设计的问题。
In many fields of medical studies, the analysis and design of repeated measurements data are often come across.
目的介绍分类数据重复测量资料的统计分析及其在临床试验中的应用。
Objective The statistical method for repeated measures categorical data analysis was introduced and applied to clinical trials.
线性混合效应模型在医学重复测量资料的数据分析与设计中广泛应用。
The linear mixed effects model in the data analysis and design of repeated measurements has been found an wide utilization in medical fields.
进行体温数据采集，就得重复测量体温，比如每秒检测一次。
Results The system could collect real-time data of temperature and write them to Micro SD.
进行体温数据采集，就得重复测量体温，比如每秒检测一次。
Results The system could collect real-time data of temperature and write them to Micro SD.
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