在广义线性混合模型框架下稀有二分类数据的随机效应Meta分析  

Random effects meta-analysis of rare binary data in the framework of the generalized linear mixed model

作　　者：吴敏[1] 郑建清[1] 黄碧芬 肖丽华[1] WU Min;ZHENG Jianqing;HUANG Bifen;XIAO Lihua(The Second Affiliated Hospital of Fujian Medical University,Quanzhou,362000,P.R.China;Quanzhou Medical College People's Hospital Affiliated,Quanzhou,362000,P.R.China)

机构地区：[1]福建医科大学附属第二医院放射治疗科,福建泉州362000 [2]福建泉州医学高等专科学校附属人民医院妇产科

出　　处：《中国循证医学杂志》2019年第7期875-882,共8页Chinese Journal of Evidence-based Medicine

基　　金：福建医科大学附属第二医院苗圃基金(编号:2017MP04)

摘　　要：稀有二分类数据的Meta分析是医学研究领域的难点,其方法学目前仍不成熟。传统的Meta分析是基于正态-正态模型的固定效应分析或随机效应分析,但这种方法仍然存在方法学上的问题。Stijnen等提出一种基于广义线性混合效应模型(generalized linear mixed model,GLMM)的确切研究内似然模型(exact within-study likelihood models,EWLM)Meta分析技术,包括二项式-正态模型(binomial-normal,BN)和超几何正态模型(hypergeometric-normal model,HNM)等,可方便地实现稀有二分类数据的随机效应Meta分析。本文结合实例介绍其在SAS软件中的实现方法,并提供相关的SAS代码。The meta-analysis of rare binary data is a difficulty in the field of medical research,and its methodology remains immature.The traditional meta-analysis technique is based on the normal-normal model of fixed effects analysis or random-effects analysis,however there are methodological problems in this method.Stijnen proposed an exact within-study likelihood models(EWLM)meta-analysis technique based on the generalized linear mixed model(GLMM),including the binomial-normal model(BN)and Hypergeometric-normal model(HNM),which can be used to achieve random effects meta-analysis of rare binary data.This paper introduces the model in detail and its implementation in SAS software with examples to provide relevant SAS code.

关 键 词：稀有数据 广义线性混合效应模型 确切研究内似然模型 正态-正态模型 二项式-正态模型 超几何正态模型 

分 类 号：R195[医药卫生—卫生统计学]