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应用SAS软件PROCMCMC过程实现网状Meta分析
引用本文:鄢金柱,;吴平勇,;张超,;刘俊,;曾宪涛.应用SAS软件PROCMCMC过程实现网状Meta分析[J].中国循证医学杂志,2014(8):1004-1008.
作者姓名:鄢金柱  ;吴平勇  ;张超  ;刘俊  ;曾宪涛
作者单位:[1]湖北医药学院附属太和医院循证医学与临床研究中心,湖北十堰442000; [2]湖北医药学院药护学院,湖北十堰442000; [3]湖北医药学院附属太和医院急诊科,湖北十堰442000; [4]成都市青羊区疾病预防控制中心,成都610031; [5]湖北医药学院循证医学教研室,湖北十堰442000
基金项目:湖北省教育科学“十二五”规划2012年度重点课题(编号2012A050),湖北医药学院附属太和医院2013年循证医学“苗圃基金”项目(编号:EBM2013004).
摘    要:SAS软件是一款功能强大、国际认可度高的编程软件,其可以实现包括网状Meta分析在内的各种Meta分析。贝叶斯统计是一种重要的统计学方法,其可以通过马尔科夫-蒙特卡洛(Markov Chain Monte Carlo,MCMC)算法进行各种统计推断。在SAS软件中运用PROC MCMC过程实现网状Meta分析正是基于这一思想进行的,本文通过实例操作展示了该过程。

关 键 词:SAS软件  PROC  MCMC过程  网状Meta分析

Application of PROC MCMC Process of SAS Software for Network Meta-Analysis
YAN Jin-zhu;WU Ping-yong;ZHANG Chao;LIU Jun;ZENG Xian-tao.Application of PROC MCMC Process of SAS Software for Network Meta-Analysis[J].Chinese Journal of Evidence-based Medicine,2014(8):1004-1008.
Authors:YAN Jin-zhu;WU Ping-yong;ZHANG Chao;LIU Jun;ZENG Xian-tao
Affiliation:YAN Jin-zhu, WU Ping-yong, ZHANG Chao, LIU Jun, ZENG Xian-tao (1. Center for Evidence-based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; 2. Institute of Medicine and Nursing, Hubei University of Medicine, Shiyan 442000, China; 3. Department of Emergency, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; 4. Center for Disease Control & Prevention of Chengdu City Qingyang District, Chengdu 610031, China; 5. Department of Evidence-based Medicine, Hubei University of Medicine, Shiyan 442000, China)
Abstract:SAS Software is a powerful and internationally-recognized programming statistical software, which can implement all kinds of meta-analysis, including network meta-analysis. Bayesian statistics is an important statistical method, which uses MCMC (Markov Chain Monte Carlo) arithmetic to conduct various statistical inference. With this idea, we implement network meta-analysis thorough PROC MCMC process and introduce this process in this article based on an example.
Keywords:SAS software  PROC MCMC process  Network meta-analysis
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