| | | 医学多变量重复观测资料的随机系数模型
| | 毕业论文下载 作者：陈长生，徐勇勇，袁天峰,赵东涛，尚磊，夏结来，潘峰
【关键词】 重复观测
Multivariate random coefficients model of repeated measures data in medical research
【Abstract】 AIM: To study multivariate random coefficients model of repeated measures data in medical research. METHODS: Both diastolic and systolic blood pressures repeated measures data, collected from 120 drug abusers after taking two kinds of medicine (Drug A: Xiaoyinfuzheng, Drug B: Kelening), were analyzed by multivariate random coefficients model. The fixed effect parameters matrix x of model coefficients were estimated by using least squares estimation method, the effects between treatment groups were compared and the variancecovariance matrices of random effect were also estimated. Related analysis methods were programmed with SAS/IML code. RESULTS: Estimated parameters with fixed effect and random effect were obtained and graphs were drawn. Both diastolic and systolic blood pressures changed with time after treatment and the trends between treatment groups were different. A slow change was observed in Drug A group, while a greater curvature was found in Drug B group. Both diastolic and systolic blood pressures in Drug A group were higher than those in Drug B group. CONCLUSION: Multivariate random coefficients model can effectively analyze the dynamic change trend and random effects of multivariate repeated measures data in medical research.
【Keywords】 repeated measures; random coefficients model; multivariate statistics
【摘要】 目的毕业论文下载：研究医学重复观测数据的毕业论文下载多变量随机系数模型. 方法：对两种药物（A药：消瘾扶正胶囊，B药：可乐宁）治疗120例患者后的舒张压和收缩压重复观测数据进行多变量随机系数模型分析，对模型系数的固定效应参数矩阵ξ作最小二乘估计并进行组间比较，同时估计随机效应的方差协方差矩阵，分析方法用SAS/IML软件编程得以实现. 结果：得到了固定效应和随机效应有关参数的估计值，并给出了曲线图. 用药后患者的舒张压和收缩压随时间的变化而变化，且两个药物组曲线的变化趋势是不相同的，A药组的变化相对平缓,而B药组起伏波动较大，用药后A药组的舒张压和收缩压相对来说均较B药组为高. 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.
【关键词】 重复观测;随机系数模型;多元统计学
0引言
医学研究中常会遇到重复观测数据的统计分析问题，例如，在临床上，为了研究不同降压药的疗效而对高血压患者服药前、服药后2, 4, 6和8 wk的血压进行重复观测；在儿少卫生中，为了研究儿童体格发育情况，定期重复观察不同喂养方式的婴儿体格发育指标，如身长、坐高、体质量等. 这类研究对个体的观察指标进行多次反复测量，其观测结果体现的是整个重复观测场合中个体指标发展变化趋势以及相关因素的影响. 由于重复观测数据间存在自相关性且随机误差至少可分为两个层次，即个体间误差和个体内反复测量间误差，因而其分析方法有别于一般的统计分析方法［1-3］. 另外，在实际工作中为了了解多个变量间的关系以及变化规律，常常需要在不同的时间点同时观测个体的多个反应变量，如收缩压和舒张压，身高和体质量等，此时，需要进行多变量分析. 为了充分利用该类数据所包含的信息以及更好地动态了解个体多个反应变量的变化规律，我们用SAS/IML软件编写了分析程序［4,5］，并对医学多变量重复观测数据进行了随机系数模型分析.
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